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Wu, Tianyou. "Art Product Recognition Model Design and Construction of VR Model." Security and Communication Networks 2022 (June 22, 2022): 1–13. http://dx.doi.org/10.1155/2022/3994102.
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The artwork embodies a profound human history and carries the essence of human civilization. Its content is complex and covers a wide range. How to use advanced technology to quickly and accurately classify and retrieve is an important research topic in the field. In our study, we first according to the requirements of practical application scenarios and existing data conditions proposed an overall scheme of artwork identification and retrieval. Through the functional analysis of the software required and the comparison of various databases, we present the system architecture design and data conceptual design, and complete the system-level planning and design. Then, the crawler grabbing process is designed to obtain artwork graphic data, the artwork dataset production process and labeling status required for the target application scenario were introduced, and the category imbalance state of the target dataset was analyzed. Moreover, the database table structure design of the artwork identification and retrieval system, design and development of each functional module of the server, and the web client was introduced. Finally, according to the organization, structure, and characteristics of virtual reality system, a product design evaluation system based on virtual reality technology was constructed. A theoretical model VR-PDES was designed for the application of virtual reality technology in product design evaluation. The results of this research are of great significance for people to search for images of unknown artworks and improve the service capabilities and service levels of scenic spots.
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Theodosiou, Zenonas, Marios Thoma, Harris Partaourides, and Andreas Lanitis. "A Systematic Approach for Developing a Robust Artwork Recognition Framework Using Smartphone Cameras." Algorithms 15, no. 9 (2022): 305. http://dx.doi.org/10.3390/a15090305.
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The provision of information encourages people to visit cultural sites more often. Exploiting the great potential of using smartphone cameras and egocentric vision, we describe the development of a robust artwork recognition algorithm to assist users when visiting an art space. The algorithm recognizes artworks under any physical museum conditions, as well as camera point of views, making it suitable for different use scenarios towards an enhanced visiting experience. The algorithm was developed following a multiphase approach, including requirements gathering, experimentation in a virtual environment, development of the algorithm in real environment conditions, implementation of a demonstration smartphone app for artwork recognition and provision of assistive information, and its evaluation. During the algorithm development process, a convolutional neural network (CNN) model was trained for automatic artwork recognition using data collected in an art gallery, followed by extensive evaluations related to the parameters that may affect recognition accuracy, while the optimized algorithm was also evaluated through a dedicated app by a group of volunteers with promising results. The overall algorithm design and evaluation adopted for this work can also be applied in numerous applications, especially in cases where the algorithm performance under varying conditions and end-user satisfaction are critical factors.
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Yang, Heekyung, Jongdae Han, and Kyungha Min. "Distinguishing Emotional Responses to Photographs and Artwork Using a Deep Learning-Based Approach." Sensors 19, no. 24 (2019): 5533. http://dx.doi.org/10.3390/s19245533.
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Visual stimuli from photographs and artworks raise corresponding emotional responses. It is a long process to prove whether the emotions that arise from photographs and artworks are different or not. We answer this question by employing electroencephalogram (EEG)-based biosignals and a deep convolutional neural network (CNN)-based emotion recognition model. We employ Russell’s emotion model, which matches emotion keywords such as happy, calm or sad to a coordinate system whose axes are valence and arousal, respectively. We collect photographs and artwork images that match the emotion keywords and build eighteen one-minute video clips for nine emotion keywords for photographs and artwork. We hired forty subjects and executed tests about the emotional responses from the video clips. From the t-test on the results, we concluded that the valence shows difference, while the arousal does not.
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Tian, Tian, and Feng Nan. "A Multitask Convolutional Neural Network for Artwork Appreciation." Mobile Information Systems 2022 (April 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/8804711.
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The computational aesthetics of pictorial art is an important part of human artistic creation, and the computational aesthetics of pictorial art images is a computationally computable human aesthetic process using machines, which has important applications and scientific significance in the automated analysis of large-scale paintings and the computational modeling of perception by machines. To this end, this paper proposes a multitask convolutional neural network model for emotion and rating of artworks. (1) An artwork appreciation dataset consisting of fifty Chinese paintings and fifty Western oil paintings was created, and twenty subjects were recruited to score the art appreciation of one hundred artworks in the dataset, covering both painting aesthetic evaluation and painting emotion evaluation. (2) Based on the artwork art appreciation dataset, an AlexNet-based convolutional neural network model is proposed to utilize the powerful feature extraction and classification capabilities of neural networks to complete artwork art appreciation, and an oversampling method and multitask learning method are used to improve the overall recognition accuracy. (3) Compared with the combination of traditional manual features + machine learning algorithms, the end-to-end multitask convolutional neural network proposed in this paper has the highest accuracy rate of 74.57%/71.43%/74.12%.
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Jiang, Dayou, and Jongweon Kim. "Artwork Recognition for Panorama Images Based on Optimized ASIFT and Cubic Projection." International Journal of Machine Learning and Computing 8, no. 1 (2018): 54–60. http://dx.doi.org/10.18178/ijmlc.2018.8.1.663.
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Brossman, Craig, and George R. Cross. "Model-based recognition of characters in trademark artwork." Pattern Recognition Letters 11, no. 5 (1990): 363–70. http://dx.doi.org/10.1016/0167-8655(90)90046-5.
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Thomas, KErstin. "The Still Life of Objects – Heidegger, Schapiro, and Derrida reconsidered." eitschrift für Ästhetik und Allgemeine Kunstwissenschaft Band 60. Heft 1 60, no. 1 (2015): 81–102. http://dx.doi.org/10.28937/1000106256.
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Kerstin Thomas revaluates the famous dispute between Martin Heidegger, Meyer Schapiro, and Jacques Derrida, concerning a painting of shoes by Vincent Van Gogh. The starting point for this dispute was the description and analysis of things and artworks developed in his essay, “The Origin of the Work of Art”. In discussing Heidegger’s account, the art historian Meyer Schapiro’s main point of critique concerned Heidegger’s claim that the artwork reveals the truth of equipment in depicting shoes of a peasant woman and thereby showing her world. Schapiro sees a striking paradox in Heidegger’s claim for truth, based on a specific object in a specific artwork while at the same time following a rather metaphysical idea of the artwork. Kerstin Thomas proposes an interpretation, which exceeds the common confrontation of philosophy versus art history by focussing on the respective notion of facticity at stake in the theoretical accounts of both thinkers. Schapiro accuses Heidegger of a lack of concreteness, which he sees as the basis for every truth claim on objects. Thomas understands Schapiro’s objections as motivated by this demand for a facticity, which not only includes the work of art, but also investigator in his concrete historical perspective. Truth claims under such conditions of facticity are always relative to historical knowledge, and open to critical intervention and therefore necessarily contingent. Following Thomas, Schapiro’s critique shows that despite his intention of giving the work of art back its autonomy, Heidegger could be accused of achieving quite the opposite: through the abstraction of the concrete, the factual, and the given to the type, he actually sets the self and the realm of knowledge of the creator as absolute and not the object of his knowledge. Instead, she argues for a revaluation of Schapiro’s position with recognition of the arbitrariness of the artwork, by introducing the notion of factuality as formulated by Quentin Meillassoux. Understood as exchange between artist and object in its concrete material quality as well as with the beholder, the truth of painting could only be shown as radically contingent. Thomas argues that the critical intervention of Derrida who discusses both positions anew is exactly motivated by a recognition of the contingent character of object, artwork and interpretation. His deconstructive analysis can be understood as recognition of the dynamic character of things and hence this could be shown with Meillassoux to be exactly its character of facticity – or factuality.
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Cetinic, Eva. "Towards Generating and Evaluating Iconographic Image Captions of Artworks." Journal of Imaging 7, no. 8 (2021): 123. http://dx.doi.org/10.3390/jimaging7080123.
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To automatically generate accurate and meaningful textual descriptions of images is an ongoing research challenge. Recently, a lot of progress has been made by adopting multimodal deep learning approaches for integrating vision and language. However, the task of developing image captioning models is most commonly addressed using datasets of natural images, while not many contributions have been made in the domain of artwork images. One of the main reasons for that is the lack of large-scale art datasets of adequate image-text pairs. Another reason is the fact that generating accurate descriptions of artwork images is particularly challenging because descriptions of artworks are more complex and can include multiple levels of interpretation. It is therefore also especially difficult to effectively evaluate generated captions of artwork images. The aim of this work is to address some of those challenges by utilizing a large-scale dataset of artwork images annotated with concepts from the Iconclass classification system. Using this dataset, a captioning model is developed by fine-tuning a transformer-based vision-language pretrained model. Due to the complex relations between image and text pairs in the domain of artwork images, the generated captions are evaluated using several quantitative and qualitative approaches. The performance is assessed using standard image captioning metrics and a recently introduced reference-free metric. The quality of the generated captions and the model’s capacity to generalize to new data is explored by employing the model to another art dataset to compare the relation between commonly generated captions and the genre of artworks. The overall results suggest that the model can generate meaningful captions that indicate a stronger relevance to the art historical context, particularly in comparison to captions obtained from models trained only on natural image datasets.
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Iliadis, Lazaros, Spyridon Nikolaidis, Panagiotis Sarigiannidis, Shaohua Wan, and Sotirios Goudos. "Artwork Style Recognition Using Vision Transformers and MLP Mixer." Technologies 10, no. 1 (2021): 2. http://dx.doi.org/10.3390/technologies10010002.
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Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the painting. In this paper, two different Deep Learning architectures—Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)—are trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset. In addition, a comparative study between the most common optimizers was conducted obtaining useful information for future studies.
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Del Chiaro, Riccardo, Andrew D. Bagdanov, and Alberto Del Bimbo. "Webly-supervised zero-shot learning for artwork instance recognition." Pattern Recognition Letters 128 (December 2019): 420–26. http://dx.doi.org/10.1016/j.patrec.2019.09.027.
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Yang and Min. "A Multi-Column Deep Framework for Recognizing Artistic Media." Electronics 8, no. 11 (2019): 1277. http://dx.doi.org/10.3390/electronics8111277.
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We present a multi-column structured framework for recognizing artistic media from artwork images. We design the column of our framework using a deep neural network. Our key idea is to recognize the distinctive stroke texture of an artistic medium, which plays a key role in distinguishing artistic media. Since stroke texture is in a local scale, the whole image is not proper for recognizing the texture. Therefore, we devise two ideas for our framework: Sampling patches from an input image and employing a Gram matrix to extract the texture. The patches sampled from an input artwork image are processed in the columns of our framework to make local decisions on the patch, and the local decisions from the patches are merged to make a final decision for the input artwork image. Furthermore, we employ a Gram matrix, which is known to effectively capture texture information, to improve the accuracy of recognition. Our framework is trained and tested using two real artwork image datasets: WikiSet of traditional artwork images and YMSet of contemporary artwork images. Finally, we build SynthSet, which is a collection of synthesized artwork images from many computer graphics literature, and propose a guideline for evaluating the synthesized artwork images.
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Hall, Peter, Hongping Cai, Qi Wu, and Tadeo Corradi. "Cross-depiction problem: Recognition and synthesis of photographs and artwork." Computational Visual Media 1, no. 2 (2015): 91–103. http://dx.doi.org/10.1007/s41095-015-0017-1.
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Tao, Zoe. "Shame and its Soundscapes." Music and Medicine 11, no. 2 (2019): 133. http://dx.doi.org/10.47513/mmd.v11i2.594.
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In this essay, I engage with issues of shame and social marginalization through “assisted” musical artworks, which combine an individual’s words with my musical accompaniment. Despite being a first-year medical student without clinical or therapeutic credentials, I generate interpretations of how collaborative, improvisatory, and informal artworks I have created as a music volunteer may assist in recognition and affirmation of one’s humanity. I present and discuss one experience in hospice care and its accompanying artwork which reflected the beauty and humanity of an individual I became close to. Additionally, I discuss more broadly how artistic creation may grant agency for people in marginalized social positions to express adverse affective and social states in their own voice. I believe that musical artworks such as these can serve to retain elements of an individual’s life and psychosocial profile that may not be directly medical in nature, but matter greatly transforming how one appraises, expresses, and resists fixed positions of shame and social stigma.
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Aerne, Annatina. "Palm Tree Whispers and Mountain Escapes: How Contemporary Artworks Contribute to an Inclusive Public Sphere." Social Inclusion 9, no. 4 (2021): 180–90. http://dx.doi.org/10.17645/si.v9i4.4180.
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How do artworks contribute to a more inclusive public sphere? Artworks contribute to the inclusiveness of a public sphere in that they help us consider previous objects as acting subjects, and thus as entities deserving membership in the public sphere. In addition, artworks typically attract a public, thus generating the necessary recognition for additional subjects. We propose a typology that categorizes artworks’ contribution to an inclusive public sphere. The typology is based on two axes: (a) artworks’ explicitness in attributing the status of a subject to a previous object and (b) the number of people that get to see the artwork. In order to illustrate the applicability of the typology and in order to understand how the two dimensions relate to one another, we analyze how two artworks include the non‐human as subjects into the public sphere: Eduardo Navarro’s Sound Mirror (shown at the 2016 São Paulo Biennal) and Prabhakar Pachpute’s Mountain Escape (exhibited in the 2016 Colombian Salón Nacional de Artistas). Comparing both artistic strategies we find that there may be a trade‐off between the explicitness and the reach of a new subjectification.
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van Paasschen, Jorien, Elisa Zamboni, Francesca Bacci, and David Melcher. "Consistent Emotions Elicited by Low-Level Visual Features in Abstract Art." Art & Perception 2, no. 1-2 (2014): 99–118. http://dx.doi.org/10.1163/22134913-00002012.
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It is often assumed that works of art have the ability to elicit emotion in their observers. An emotional response to a visual stimulus can occur as early as 120 ms after stimulus onset, before object categorisation can take place. This implies that emotions elicited by an artwork may depend in part on bottom-up processing of its visual features (e.g., shape, colour, composition) and not just on object recognition or understanding of artistic style. We predicted that participants are able to judge the emotion conveyed by an artwork in a manner that is consistent across observers. We tested this hypothesis using abstract paintings; these do not provide any reference to objects or narrative contexts, so that any perceived emotion must stem from basic visual characteristics. Nineteen participants with no background in art rated 340 abstract artworks from different artistic movements on valence and arousal on a Likert scale. An intra-class correlation model showed a high consistency in ratings across observers. Importantly, observers used the whole range of the rating scale. Artworks with a high number of edges (complex) and dark colours were rated as more arousing and more negative compared to paintings containing clear lines, bright colours and geometric shapes. These findings provide evidence that emotions can be captured in a meaningful way by the artist in a set of low-level visual characteristics, and that observers interpret this emotional message in a consistent, uniform manner.
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Wan, Jixin, and Yu Xiaobo. "Intelligent Retrieval Method of Approximate Painting in Digital Art Field." Scientific Programming 2021 (November 20, 2021): 1–8. http://dx.doi.org/10.1155/2021/5796600.
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With the rapid development of Internet technology and the wide application of image acquisition equipment, the number of digital artwork images is exploding. The retrieval of near-similar artwork images has a wide application prospect for copyright infringement, trademark registration, and other scenes. However, compared with traditional images, these artwork images have the characteristics of high similarity and complexity, which lead to the retrieval accuracy not meeting the demand. To solve the above problems, an intelligent retrieval method of artwork image based on wavelet transform and dual propagation neural network (WTCPN) is proposed. Firstly, the original artwork image is replaced by the low-frequency subimage after wavelet transform, which not only removes redundant information and reduces the dimension of data but also suppresses random noise. Secondly, in order to make the network assign different competition winning units to different types of modes, the dual propagation neural network is improved by setting the maximum number of times of winning neurons. Experimental results show that the proposed method can improve the accuracy of image retrieval, and the recognition accuracy of verification set can reach over 91%.
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Jabbar, Muhammad Shahid, Jitae Shin, and Jun-Dong Cho. "AI Ekphrasis: Multi-Modal Learning with Foundation Models for Fine-Grained Poetry Retrieval." Electronics 11, no. 8 (2022): 1275. http://dx.doi.org/10.3390/electronics11081275.
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Artificial intelligence research in natural language processing in the context of poetry struggles with the recognition of holistic content such as poetic symbolism, metaphor, and other fine-grained attributes. Given these challenges, multi-modal image–poetry reasoning and retrieval remain largely unexplored. Our recent accessibility study indicates that poetry is an effective medium to convey visual artwork attributes for improved artwork appreciation of people with visual impairments. We, therefore, introduce a deep learning approach for the automatic retrieval of poetry suitable to the input images. The recent state-of-the-art CLIP provides a way for multi-modal visual and text features matched using cosine similarity. However, it lacks shared cross-modality attention features to model fine-grained relationships. The proposed approach in this work takes advantage of strong pre-training of the CLIP model and overcomes its limitations by introducing shared attention parameters to better model the fine-grained relationship between both modalities. We test and compare our proposed approach using the expertly annotated MiltiM-Poem dataset, which is considered the largest public image–poetry pair dataset for English poetry. The proposed approach aims to solve the problems of image-based attribute recognition and automatic retrieval for fine-grained poetic verses. The test results reflect that the shared attention parameters alleviate fine-grained attribute recognition, and the proposed approach is a significant step towards automatic multi-modal retrieval for improved artwork appreciation of people with visual impairments.
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Chen, Haibo, Lei Zhao, Lihong Qiu, et al. "Creative and diverse artwork generation using adversarial networks." IET Computer Vision 14, no. 8 (2020): 650–57. http://dx.doi.org/10.1049/iet-cvi.2020.0014.
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Philipp-Foliguet, Sylvie, Michel Jordan, Laurent Najman, and Jean Cousty. "Artwork 3D model database indexing and classification." Pattern Recognition 44, no. 3 (2011): 588–97. http://dx.doi.org/10.1016/j.patcog.2010.09.016.
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Pasqualino, Giovanni, Antonino Furnari, Giovanni Signorello, and Giovanni Maria Farinella. "An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites." Image and Vision Computing 107 (March 2021): 104098. http://dx.doi.org/10.1016/j.imavis.2021.104098.
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Gao, Yang, Neng Chang, and Kai Shang. "Multi-layer and multi-order fine-grained feature learning for artwork attribute recognition." Computer Communications 173 (May 2021): 214–19. http://dx.doi.org/10.1016/j.comcom.2021.03.006.
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Shyrman, Roman. "Video Surveillance as an Educational Exercise and Artwork." Bulletin of Kyiv National University of Culture and Arts. Series in Audiovisual Art and Production 5, no. 1 (2022): 28–37. http://dx.doi.org/10.31866/2617-2674.5.1.2022.256949.
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The purpose of the article is to analyze the importance of training exercises in video surveillance for the creative abilities’ development of film and television directors; to prove the necessity and usefulness of such exercises not only for documentarians but also for feature film and animation directors; identify specific methods of the director’s work on video surveillance. The research methodology is based on a theoretical analysis of the work of outstanding film directors, in particular films and evidence on the nature of documentary films by Hertz Frank and Frederick Wiseman and analysis of Ukrainian and foreign observation films. Scientific novelty. The role recognition of film and video surveillance as a basic element in the education and training of cinematographers; determination of characteristic features and fundamental differences of work on screen observations in comparison with work on other types of the screen works. Conclusions. The article analyzes the importance of video surveillance for the creative imagination development of students-directors. The importance of observations has been proved for the work of directors working in all types of cinematography from documentaries to feature films and animation. Examples of directorial work strategies on video surveillance are given, which are fundamentally different from the methods of creating other types of screen works.
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Kloppmann, W., L. Leroux, P. Bromblet, et al. "Competing English, Spanish, and French alabaster trade in Europe over five centuries as evidenced by isotope fingerprinting." Proceedings of the National Academy of Sciences 114, no. 45 (2017): 11856–60. http://dx.doi.org/10.1073/pnas.1707450114.
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A lack of written sources is a serious obstacle in the reconstruction of the medieval trade of art and art materials, and in the identification of artists, workshop locations, and trade routes. We use the isotopes of sulfur, oxygen, and strontium (S, O, Sr) present in gypsum alabaster to unambiguously link ancient European source quarries and areas to alabaster artworks produced over five centuries (12th–17th) held by the Louvre museum in Paris and other European and American collections. Three principal alabaster production areas are identified, in central England, northern Spain, and a major, long-lived but little-documented alabaster trade radiating from the French Alps. The related trade routes are mostly fluvial, although terrestrial transport crossing the major river basin borders is also confirmed by historical sources. Our study also identifies recent artwork restoration using Italian alabaster and provides a robust geochemical framework for provenancing, including recognition of restoration and forgeries.
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Reysen, Stephen, Courtney N. Plante, Sharon E. Roberts, and Kathleen C. Gerbasi. "Fan and Non-Fan Recollection of Faces in Fandom-Related Art and Costumes." Journal of Cognition and Culture 18, no. 1-2 (2018): 224–29. http://dx.doi.org/10.1163/15685373-12340024.
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Abstract We compared face recognition of humans and fandom-themed characters (art and costumes) between a sample of furries (fans of anthropomorphic animal art) and non-furries. Participants viewed images that included humans, drawn anthropomorphic animals, and anthropomorphic animal costumes, and were later tested on their ability to recognize faces from a subset of the viewed images. While furries and non-furries did not differ in their recollection of human faces, furries showed significantly better memory for faces in furry-themed artwork and costumes. The results are discussed in relation to own-group bias in face recognition.
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Milani, Federico, Nicolò Oreste Pinciroli Pinciroli Vago, and Piero Fraternali. "Proposals Generation for Weakly Supervised Object Detection in Artwork Images." Journal of Imaging 8, no. 8 (2022): 215. http://dx.doi.org/10.3390/jimaging8080215.
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Object Detection requires many precise annotations, which are available for natural images but not for many non-natural data sets such as artworks data sets. A solution is using Weakly Supervised Object Detection (WSOD) techniques that learn accurate object localization from image-level labels. Studies have demonstrated that state-of-the-art end-to-end architectures may not be suitable for domains in which images or classes sensibly differ from those used to pre-train networks. This paper presents a novel two-stage Weakly Supervised Object Detection approach for obtaining accurate bounding boxes on non-natural data sets. The proposed method exploits existing classification knowledge to generate pseudo-ground truth bounding boxes from Class Activation Maps (CAMs). The automatically generated annotations are used to train a robust Faster R-CNN object detector. Quantitative and qualitative analysis shows that bounding boxes generated from CAMs can compensate for the lack of manually annotated ground truth (GT) and that an object detector, trained with such pseudo-GT, surpasses end-to-end WSOD state-of-the-art methods on ArtDL 2.0 (≈41.5% mAP) and IconArt (≈17% mAP), two artworks data sets. The proposed solution is a step towards the computer-aided study of non-natural images and opens the way to more advanced tasks, e.g., automatic artwork image captioning for digital archive applications.
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Marnin-Distelfeld, Shahar, and Uri Dorchin. "“I AM NOT AN ARTIST, I MAKE ART”: AMATEURISH ARTISTS IN ISRAEL AND THE SENSE OF CREATIVITY." Creativity Studies 13, no. 1 (2020): 64–86. http://dx.doi.org/10.3846/cs.2020.9907.
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This study deals with self-taught visual artists who are considered “amateurish” by the establishment of the Memorial Center in Kiryat Tiv’on, Israel, where they have exhibit their artwork. We will try to figure out both the explicit and implicit characteristics of “amateurish” artists, and challenge the supposed linkage between amateurism and lack of creativity. The methodology applied combines a sociological point of view, drawing on in-depth interviews with the artists, along with a visual analysis of the artwork produced. The theory of “modest” artists, by Marie Buscatto, and the theory of serious leisure perspective by Robert A. Stebbins, will contribute supportive classifications and categories for the analysis. We claim that the artists of our study are located on an axis between “amateurish” and “professional” within a fluid area of “serious leisure”. They are regarded as “amateurish” due to their lack of academic background in the arts, their relatively old age, having encountered lack of official recognition, having come across various obstacles in displaying their art and having received low remunerations. Aside from their marginal position in the art field, we were able to detect a few characteristics that distinguish their artwork from that of “professionals”. Our findings prove them to constitute an in-between category of “modest” or “serious-leisure-amateurish” artists, which blurs the dichotomy between “amateurish” and “professional” artists imposed by the establishment. We found these “modest” artists’ experiences to be creative, as well as some of their artwork; nevertheless, this kind of creativity seems to be disregarded by the establishment which perceives creativity as innovation.
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Jabbar, Muhammad Shahid, Chung-Heon Lee, and Jun Dong Cho. "ColorWatch: Color Perceptual Spatial Tactile Interface for People with Visual Impairments." Electronics 10, no. 5 (2021): 596. http://dx.doi.org/10.3390/electronics10050596.
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Tactile perception enables people with visual impairments (PVI) to engage with artworks and real-life objects at a deeper abstraction level. The development of tactile and multi-sensory assistive technologies has expanded their opportunities to appreciate visual arts. We have developed a tactile interface based on the proposed concept design under considerations of PVI tactile actuation, color perception, and learnability. The proposed interface automatically translates reference colors into spatial tactile patterns. A range of achromatic colors and six prominent basic colors with three levels of chroma and values are considered for the cross-modular association. In addition, an analog tactile color watch design has been proposed. This scheme enables PVI to explore artwork or real-life object color by identifying the reference colors through a color sensor and translating them to the tactile interface. The color identification tests using this scheme on the developed prototype exhibit good recognition accuracy. The workload assessment and usability evaluation for PVI demonstrate promising results. This suggest that the proposed scheme is appropriate for tactile color exploration.
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Milani, Federico, and Piero Fraternali. "A Dataset and a Convolutional Model for Iconography Classification in Paintings." Journal on Computing and Cultural Heritage 14, no. 4 (2021): 1–18. http://dx.doi.org/10.1145/3458885.
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Iconography in art is the discipline that studies the visual content of artworks to determine their motifs and themes and to characterize the way these are represented. It is a subject of active research for a variety of purposes, including the interpretation of meaning, the investigation of the origin and diffusion in time and space of representations, and the study of influences across artists and artworks. With the proliferation of digital archives of art images, the possibility arises of applying Computer Vision techniques to the analysis of art images at an unprecedented scale, which may support iconography research and education. In this article, we introduce a novel paintings dataset for iconography classification and present the quantitative and qualitative results of applying a Convolutional Neural Network ( CNN ) classifier to the recognition of the iconography of artworks. The proposed classifier achieves good performances (71.17% Precision, 70.89% Recall, 70.25% F1-Score, and 72.73% Average Precision) in the task of identifying saints in Christian religious paintings, a task made difficult by the presence of classes with very similar visual features. Qualitative analysis of the results shows that the CNN focuses on the traditional iconic motifs that characterize the representation of each saint and exploits such hints to attain correct identification. The ultimate goal of our work is to enable the automatic extraction, decomposition, and comparison of iconography elements to support iconographic studies and automatic artwork annotation.
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VOEGELIN, SALOMÉ. "Sonic memory material as ‘pathetic trigger’." Organised Sound 11, no. 1 (2006): 13–18. http://dx.doi.org/10.1017/s1355771806000033.
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Memory, according to Henri Bergson, is gleaned from the present and realises the present perception from its sensory-motor elements through movements towards that which it perceives.The purpose of this article is to propose and debate the deliberate use of such ‘present memory’ in the sonic artwork. The suggestion is that sonic memory material – sounds that are plundered from old recordings – can be collaged into complex sonic works to produce, not a nostalgic experience in the sense of a recognition of the past, but a current production of sonic material in a continually present perception. Such a production strategy employs the affective quality of memory to ‘trigger’ a sensorial engagement in the sense of a ‘pathetic’ engagement understood as an emotional and sentimental involvement with the work. The understanding is that such an emotional engagement involves the listener centrally in the production of the artwork and challenges modernist (visual) art discourses, which evaluate the work from a distance.
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Fuxjäger, Anton. "Translation, Emphasis, Synthesis, Disturbance: On the function of music in visual music." Organised Sound 17, no. 2 (2012): 120–27. http://dx.doi.org/10.1017/s1355771812000040.
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Starting from the premiss that the central aesthetic feature of non-representational moving images (visual music) is their structuring of reception time, the function of the accompanying music in contributing to the total (combined) temporal structure of the resulting artwork is discussed. A taxonomy of the different roles that music can play in the production and reception of visual music consisting of three basic categories is presented and examples are given:•‘Music translations’: certain parameters of the accompanying music are transcoded into certain visual parameters, the accompanying music thereby provides the temporal structure of the audiovisual artwork.•‘Synthetic structures’: the music and the images provide different temporal informations with enough coincidences to be synthesised into a combined audiovisual strucuture by the viewer/listener.•‘Mutual disturbance’: the aforementioned process fails to be realised due to a lack of sufficient points of synchronisation. As a result the accompanying music will disrupt the recognition of the temporal structure of the images and vice versa.
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Yang, Heekyung, and Kyungha Min. "A Saliency-Based Patch Sampling Approach for Deep Artistic Media Recognition." Electronics 10, no. 9 (2021): 1053. http://dx.doi.org/10.3390/electronics10091053.
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We present a saliency-based patch sampling strategy for recognizing artistic media from artwork images using a deep media recognition model, which is composed of several deep convolutional neural network-based recognition modules. The decisions from the individual modules are merged into the final decision of the model. To sample a suitable patch for the input of the module, we devise a strategy that samples patches with high probabilities of containing distinctive media stroke patterns for artistic media without distortion, as media stroke patterns are key for media recognition. We design this strategy by collecting human-selected ground truth patches and analyzing the distribution of the saliency values of the patches. From this analysis, we build a strategy that samples patches that have a high probability of containing media stroke patterns. We prove that our strategy shows best performance among the existing patch sampling strategies and that our strategy shows a consistent recognition and confusion pattern with the existing strategies.
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Masiero, A., G. Tucci, A. Conti, L. Fiorini, and A. Vettore. "INITIAL EVALUATION OF THE POTENTIAL OF SMARTPHONE STEREO-VISION IN MUSEUM VISITS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W11 (May 5, 2019): 837–42. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w11-837-2019.
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<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>
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Wicaksono, Singgih Prio. "VISUAL STRATEGIES OF CONTEMPORARY ART: A Case Study of Banksy’s Artworks." Journal of Urban Society's Arts 7, no. 1 (2020): 9–14. http://dx.doi.org/10.24821/jousa.v7i1.3924.
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Visual Strategy of Contemporary Art: The Study of Banksy’s Artwork. The development of contemporary art has introduced a new understanding and recognition of esthetics. This article aims to describe postesthetic phenomena as trends in the visual communication of contemporary art. The method used is a descriptive approach and analysis of Banksy's work. This study produces a discussion about: 1). Postesthetic symptoms in Banksy's work, 2). Characteristics of Banksy's work, 3). Banksy's symbolic meaning, 3). Social implications arising from the postesthetic approach to Banksy's work. Keywords: visual language, consumerism, contemporary art
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KIM, Sa-Ra. "What Is the Reason for Learning Art?: Changes of Learner’s Recognition on Art through Art Expression Teaching." Korean Association For Learner-Centered Curriculum And Instruction 22, no. 15 (2022): 575–90. http://dx.doi.org/10.22251/jlcci.2022.22.15.575.
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Objectives This study started from the fact that confinement in the formalism of art expression cannot persuade students to answer the question of ‘What is the reason for learning art?’. Hence, the purpose of this study is to clarify whether learner’s recognition on art can be changed through the case on teaching art expression.
 Methods This study is done for the objects of the three 6th graders with insufficient confidence in practical skills in art. The researcher planned and practiced art expression class for one 6th grader and analyzed the study result by focusing on the student’s work and the interview details. ‘What type of person am I?’ and ‘What type of person will I want to be?’ are presented as subjects, and the artwork was planned and produced through the story-telling of the student from plan preparation. Only one student’s (alias-Ayeong) work is used with the content of the interview with the student as data due to the limit of space to understand a typical case and do analysis as the qualitative case study on researching the culture pattern.
 Results A-yeong recognized art as ‘the thing not requiring the use of her head’, ‘making a thing’, and ‘the thing that is not study’ in the pre-interview and was doing an art activity like that of a kindergartener or a low grader even though she was a high grader in the elementary school. Before the actual class, she selected the best photo expressing her to talk about herself and provide the prior experience connecting the meaning and the image. She made the acrylics entitled ‘Vine’ through storytelling and expressed the mind of becoming a warm person to people around her with the huge pot decorated with the vine, the rocker, etc. The changes of learner’s recognition on art could be checked after artwork production. Those changes are ‘A drawing plays the role not replaced by a photo.’, ‘Finding self through art expression’, ‘A good artwork is unique and satisfying.’, and ‘The scope of art expression is wider than that of writing’.
 Conclusions First, conversation with a student helps a student organize the meaning suitable to the subjects and properly implement the meaning with the formative language. Second, the art creation of an upper elementary school grader should be the creative activity based on the higher quest for the life of self beyond the level of an infantile art activity. Third, the meaning of learning art is convincing only if a teacher cannot directly teach it but a student should experience and realize it for itself.
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Cook, Jenny, Nina Fudge, Eleanor Stevens, and Christopher McKevitt. "Stroke through a lens: Exposing the challenges of establishing a visual arts project as a research engagement activity." Research for All 1, no. 1 (2017): 84–105. http://dx.doi.org/10.18546/rfa.01.1.07.
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To celebrate 20 years of an epidemiological study, the South London Stroke Register, we collaborated with student artists and stroke survivors to create an exhibition of visual arts displayed at a series of events in 2015–16. This paper explores the expectations placed on researchers to engage with different publics, touching on current debates around institutional support and recognition. We critically reflect on the project process, identifying challenges and offering recommendations. We include the perspectives of the stroke survivors and the student artists, and examples of the artwork.
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Hien, Ngo Le Huy, Luu Van Huy, and Nguyen Van Hieu. "Artwork style transfer model using deep learning approach." Cybernetics and Physics, Volume 10, 2021, Number 3 (October 30, 2021): 127–37. http://dx.doi.org/10.35470/2226-4116-2021-10-3-127-137.
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Art in general and fine arts, in particular, play a significant role in human life, entertaining and dispelling stress and motivating their creativeness in specific ways. Many well-known artists have left a rich treasure of paintings for humanity, preserving their exquisite talent and creativity through unique artistic styles. In recent years, a technique called ’style transfer’ allows computers to apply famous artistic styles into the style of a picture or photograph while retaining the shape of the image, creating superior visual experiences. The basic model of that process, named ’Neural Style Transfer,’ has been introduced promisingly by Leon A. Gatys; however, it contains several limitations on output quality and implementation time, making it challenging to apply in practice. Based on that basic model, an image transform network was proposed in this paper to generate higher-quality artwork and higher abilities to perform on a larger image amount. The proposed model significantly shortened the execution time and can be implemented in a real-time application, providing promising results and performance. The outcomes are auspicious and can be used as a referenced model in color grading or semantic image segmentation, and future research focuses on improving its applications.
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Aspinall, Peter J. "Social Representations of Art in Public Places: A Study of Everyday Explanations of the Statue of ‘A Real Birmingham Family’." Genealogy 5, no. 3 (2021): 59. http://dx.doi.org/10.3390/genealogy5030059.
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This article focuses on the social/cultural representations of the statue of A Real Birmingham Family cast in bronze and unveiled in Britain’s second city in October 2014. It reveals a family comprising two local mixed-race sisters, both single mothers, and their sons, unanimously chosen from 372 families. Three of the four families shortlisted for the statue were ‘mixed-race’ families. The artwork came about through a partnership between the sculptress, Gillian Wearing, and the city’s Ikon Gallery. A number of different lay representations of the artwork have been identified, notably, that it is a ‘normal family with no fathers’ and that it is not a ‘typical family’. These are at variance with a representation based on an interpretation of the artwork and materials associated with its creation: that a nuclear family is one reality amongst many and that what constitutes a family should not be fixed. This representation destabilizes our notion of the family and redefines it as empirical, experiential, and first-hand, families being brought into recognition by those in the wider society who choose to nominate themselves as such. The work of Ian Hacking, Richard Jenkins, and others is drawn upon to contest the concept of ‘normality’. Further, statistical data are presented that show that there is now a plurality of family types with no one type dominating or meriting the title of ‘normal’. Finally, Wearing’s statues of families in Trentino and Copenhagen comprise an evolving body of cross-national public art that provides further context and meaning for this representation.
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Schreiber, Rebecca M. "The Work of Arte Urgente." Latin American and Latinx Visual Culture 4, no. 3 (2022): 23–43. http://dx.doi.org/10.1525/lavc.2022.4.3.23.
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This essay examines how migrant/refugee youth from Central America use their bodies as part of collaborative performances in which they narrate their experiences as social actors within the context of the so-called “child migrant crisis.” In Arte Urgente (Urgent Art) workshops organized by Caleb Duarte with students from Fremont High School’s Newcomer Education Support and Transition (NEST) Program, they created performances in which they staged a response to the structural conditions that compelled them to migrate and that shaped their everyday lives. The emphasis on performance resonates with the experience of these young people, who have to act, perform, and consciously play to a variety of specific audiences starting from the time they leave home. In addition to these performances, they also created a public artwork, the Embassy of the Refugee, in which they enact a performative agency, rather than seeking recognition from the US settler state. Although these migrant/refugee youth are for the most part excluded from having political agency within the process of applying for asylum, I argue that through their artwork they imagine other possibilities for themselves and for others outside the purview of state policies.
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Cho, Jun-Dong, and Yong Lee. "ColorPoetry: Multi-Sensory Experience of Color with Poetry in Visual Arts Appreciation of Persons with Visual Impairment." Electronics 10, no. 9 (2021): 1064. http://dx.doi.org/10.3390/electronics10091064.
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Visually impaired visitors experience many limitations when visiting museum exhibits, such as a lack of cognitive and sensory access to exhibits or replicas. Contemporary art is evolving in the direction of appreciation beyond simply looking at works, and the development of various sensory technologies has had a great influence on culture and art. Thus, opportunities for people with visual impairments to appreciate visual artworks through various senses such as hearing, touch, and smell are expanding. However, it is uncommon to provide a multi-sensory interactive interface for color recognition, such as integrating patterns, sounds, temperature, and scents. This paper attempts to convey a color cognition to the visually impaired, taking advantage of multisensory coding color. In our previous works, musical melodies with different combinations of pitch, timbre, velocity, and tempo were used to distinguish vivid (i.e., saturated), light, and dark colors. However, it was rather difficult to distinguish among warm/cool/light/dark colors with using sound cues only. Therefore, in this paper, we aim to build a multisensory color-coding system with combining sound and poem such that poem leads to represent more color dimensions, such as including warm and cool colors for red, orange, yellow, green, blue, and purple. To do this, we first performed an implicit association test to identify the most suitable poem among the candidate poems to represent colors in artwork by finding the common semantic directivity between the given candidate poem with voice modulation and the artwork in terms of light/dark/warm/color dimensions. Finally, we conducted a system usability test on the proposed color-coding system, confirming that poem will be an effective supplement for distinguishing between vivid, light, and dark colors with different color appearance dimensions, such as warm and cold colors. The user experience score of 15 college students was 75.1%, that was comparable with the color-music coding system that received a user experience rating of 74.1%. with proven usability.
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Andrea Orlando, Santi, Antonino Furnari, and Giovanni Maria Farinella. "Egocentric visitor localization and artwork detection in cultural sites using synthetic data." Pattern Recognition Letters 133 (May 2020): 17–24. http://dx.doi.org/10.1016/j.patrec.2020.02.014.
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Pinciroli Vago, Nicolò Oreste Pinciroli, Federico Milani, Piero Fraternali, and Ricardo da Silva Torres. "Comparing CAM Algorithms for the Identification of Salient Image Features in Iconography Artwork Analysis." Journal of Imaging 7, no. 7 (2021): 106. http://dx.doi.org/10.3390/jimaging7070106.
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Iconography studies the visual content of artworks by considering the themes portrayed in them and their representation. Computer Vision has been used to identify iconographic subjects in paintings and Convolutional Neural Networks enabled the effective classification of characters in Christian art paintings. However, it still has to be demonstrated if the classification results obtained by CNNs rely on the same iconographic properties that human experts exploit when studying iconography and if the architecture of a classifier trained on whole artwork images can be exploited to support the much harder task of object detection. A suitable approach for exposing the process of classification by neural models relies on Class Activation Maps, which emphasize the areas of an image contributing the most to the classification. This work compares state-of-the-art algorithms (CAM, Grad-CAM, Grad-CAM++, and Smooth Grad-CAM++) in terms of their capacity of identifying the iconographic attributes that determine the classification of characters in Christian art paintings. Quantitative and qualitative analyses show that Grad-CAM, Grad-CAM++, and Smooth Grad-CAM++ have similar performances while CAM has lower efficacy. Smooth Grad-CAM++ isolates multiple disconnected image regions that identify small iconographic symbols well. Grad-CAM produces wider and more contiguous areas that cover large iconographic symbols better. The salient image areas computed by the CAM algorithms have been used to estimate object-level bounding boxes and a quantitative analysis shows that the boxes estimated with Grad-CAM reach 55% average IoU, 61% GT-known localization and 31% mAP. The obtained results are a step towards the computer-aided study of the variations of iconographic elements positioning and mutual relations in artworks and open the way to the automatic creation of bounding boxes for training detectors of iconographic symbols in Christian art images.
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Mather, George. "Aesthetic Judgement of Orientation in Modern Art." i-Perception 3, no. 1 (2012): 18–24. http://dx.doi.org/10.1068/i0447aap.
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When creating an artwork, the artist makes a decision regarding the orientation at which the work is to be hung based on their aesthetic judgement and the message conveyed by the piece. Is the impact or aesthetic appeal of a work diminished when it is hung at an incorrect orientation? To investigate this question, Experiment 1 asked whether naïve observers can appreciate the correct orientation (as defined by the artist) of 40 modern artworks, some of which are entirely abstract. Eighteen participants were shown 40 paintings in a series of trials. Each trial presented all four cardinal orientations on a computer screen, and the participant was asked to select the orientation that was most attractive or meaningful. Results showed that the correct orientation was selected in 48% of trials on average, significantly above the 25% chance level, but well below perfect performance. A second experiment investigated the extent to which the 40 paintings contained recognisable content, which may have mediated orientation judgements. Recognition rates varied from 0% for seven of the paintings to 100% for five paintings. Orientation judgements in Experiment 1 correlated significantly with “meaningful” content judgements in Experiment 2: 42% of the variance in orientation judgements in Experiment 1 was shared with recognition of meaningful content in Experiment 2. For the seven paintings in which no meaningful content at all was detected, 41% of the variance in orientation judgements was shared with variance in a physical measure of image content, Fourier amplitude spectrum slope. For some paintings, orientation judgements were quite consistent, despite a lack of meaningful content. The origin of these orientation judgements remains to be identified.
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Buddeus, Hana. "Enlarged Details and Close-up Views: Art Reproduction in 1930s Czechoslovakia." Artium Quaestiones, no. 33 (December 30, 2022): 61–86. http://dx.doi.org/10.14746/aq.2022.33.3.
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Each photograph captures an artwork within a particular frame of space and time, providing a perspective that is contingent and dependent on the era the photograph was made in (Bergstein 1992). Moreover, every photograph is always embedded in specific material conditions and has its own social life (Edwards–Hart 2004). The aim of this article is to show the particularity of reproductions of artworks in 1930s Czechoslovakia and the motivations and discussions behind the extensive use of detail. I argue that the pronounced interest in close-up views is a result of a series of circumstances specific to the period. There is an important pre-condition in the development in the field of art photography and graphic design that took place in the late 1920s, bringing about an interest in sharp and faithful images and full bleed prints, as well as a recognition of the social impact of the medium. As a result, photographers, artists, art historians, and graphic designers living in Czechoslovakia also began to rethink the use of photography in the art field. This was manifested in period publications such as the well-known Fotografie vidí povrch (Photography Sees the Surface), published in 1935. In terms of art reproductions, it shows the importance of close-up views for providing an insight into individual artistic approaches and into the history of the respective artwork. The same year saw the publication of the 31st volume of the art magazine Volné směry, which enables us to follow several micro-histories that can also be applied more generally to the period discussions. As illustrated by a text by Bohuslav Slánský and the reproduced photographs of medieval panel portraits from Karlštejn Castle attributed to Master Theodoric, one of the purposes behind the commissions of enlarged photographic details of artworks were planned restorations. Moreover, examples from the photographic campaigns led by the company of Jan Štenc, the State Photo-Measurement Institute, or the project by Karel Šourek, Alexandr Paul, and František Illek (Documenta Bohemia Artis Phototypica) show that detail is generally used for showing the structure and texture of the work, for zooming in on otherwise distant works, or for the purpose of comparison. According to Volné směry editor-in-chief Emil Filla and his manifesto article “Práce oka”, the new method of working with reproductions and the frequent use of photographic detail precipitated a change in the observational habits of the audience. This intention was materialised through his long-term collaboration with the photographer Josef Sudek, who helped him show the artworks in a new light. It is evident that by the mid-1930s, the synergic work of individuals from different fields brought the use of detail in art-related publications to an unprecedented level.
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Boulton, Padraig, and Peter Hall. "Under Material Skin Lie the Bones of Identity." Art and Perception 8, no. 3-4 (2020): 387–406. http://dx.doi.org/10.1163/22134913-bja10020.
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This paper explores the automated recognition of objects and materials and their relation to depictions in images of all kinds: photographs, artwork, doodles by children, and any other visual representation. The way artists of all cultures, ages and skill levels depict objects and materials furnishes a gamut of ‘depictions’ so wide as to present a severe challenge to current algorithms — none of them perform satisfactorily across any but a few types of depiction. Indeed, most algorithms exhibit a significant performance loss when the images used are non photographic in nature. This loss can be explained using the tacit assumptions that underlay nearly every algorithm for recognition. Appeal to the art history literature provides an alternative set of assumptions, that are more robust to variations in depiction and which offer new ways forward for automated image analysis. This is important, not just to advance computer vision, but because of the new understanding and applications that it opens.
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Moualla, Aliaa, Sofiane Boucenna, Ali Karaouzene, Denis Vidal, and Philippe Gaussier. "Is it useful for a robot to visit a museum?" Paladyn, Journal of Behavioral Robotics 9, no. 1 (2018): 374–90. http://dx.doi.org/10.1515/pjbr-2018-0025.
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AbstractIn this work, we study how learning in a special environment such as a museum can influence the behavior of robots. More specifically, we show that online learning based on interaction with people at a museum leads the robots to develop individual preferences. We first developed a humanoid robot (Berenson) that has the ability to head toward its preferred object and to make a facial expression that corresponds to its attitude toward said object. The robot is programmed with a biologically-inspired neural network sensory-motor architecture. This architecture allows Berenson to learn and to evaluate objects. During experiments, museum visitors’ emotional responses to artworks were recorded and used to build a database for training. A similar database was created in the laboratory with laboratory objects. We use those databases to train two simulated populations of robots. Each simulated robot emulates the Berenson sensory-motor architecture. Firstly, the results show the good performance of our architecture in artwork recognition in the museum. Secondly, they demonstrate the effect of training variability on preference diversity. The response of the two populations in a new unknown environment is different; the museum population of robots shows a greater variance in preferences than the population of robots that have been trained only on laboratory objects. The obtained diversity increases the chances of success in an unknown environment and could favor an accidental discovery.
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Lee, Isack, and Seok Bong Yoo. "Latent-PER: ICA-Latent Code Editing Framework for Portrait Emotion Recognition." Mathematics 10, no. 22 (2022): 4260. http://dx.doi.org/10.3390/math10224260.
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Although real-image emotion recognition has been developed in several studies, an acceptable accuracy level has not been achieved in portrait drawings. This paper proposes a portrait emotion recognition framework based on independent component analysis (ICA) and latent codes to overcome the performance degradation problem in drawings. This framework employs latent code extracted through a generative adversarial network (GAN)-based encoder. It learns independently from factors that interfere with expression recognition, such as color, small occlusion, and various face angles. It is robust against environmental factors since it filters latent code by adding an emotion-relevant code extractor to extract only information related to facial expressions from the latent code. In addition, an image is generated by changing the latent code to the direction of the eigenvector for each emotion obtained through the ICA method. Since only the position of the latent code related to the facial expression is changed, there is little external change and the expression changes in the desired direction. This technique is helpful for qualitative and quantitative emotional recognition learning. The experimental results reveal that the proposed model performs better than the existing models, and the latent editing used in this process suggests a novel manipulation method through ICA. Moreover, the proposed framework can be applied for various portrait emotion applications from recognition to manipulation, such as automation of emotional subtitle production for the visually impaired, understanding the emotions of objects in famous classic artwork, and animation production assistance.
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DELANY, CLARE, and HEATHER GAUNT. "“I Left the Museum Somewhat Changed”: Visual Arts and Health Ethics Education." Cambridge Quarterly of Healthcare Ethics 27, no. 3 (2018): 511–24. http://dx.doi.org/10.1017/s0963180117000913.
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Abstract:A common goal of ethics education is to equip students who later become health practitioners to not only know about the ethical principles guiding their practice, but to also autonomously recognize when and how these principles might apply and assist these future practitioners in providing care for patients and families. This article aims to contribute to discussions about ethics education pedagogy and teaching, by presenting and evaluating the use of the visual arts as an educational approach designed to facilitate students’ moral imagination and independent critical thinking about ethics in clinical practice. We describe a sequence of ethics education strategies over a 3 year Doctor of Physiotherapy program, focusing on the final year professional ethics assessment task, which involved the use of visual arts to stimulate the exploration of ethics in healthcare. The data (in the form of student essays about their chosen artwork) were analyzed using both thematic and content analysis. Two key themes centered on emotional responses and lateral thinking. The use of artwork appeared to facilitate imaginative, emotional, and conceptual thinking about ethics and clinical experience (both past and future). This study provides some evidence to support the effectiveness of the use of the visual arts in promoting students’ recognition of ethical dimensions within their clinical experience and reflection on their emerging professional identity. As one student noted, she left the museum “somewhat changed.”
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Howell, Richard D., Patrick B. Scott, and Jeffrey Diamond. "The Effects of “Instant” Logo Computing Language on the Cognitive Development of Very Young Children." Journal of Educational Computing Research 3, no. 2 (1987): 249–60. http://dx.doi.org/10.2190/a0qk-hb7a-rxqb-70nc.
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This study was designed to investigate whether the use of Logo accelerates the cognitive development of five- to seven-year-old children in a kindergarten class as measured by Piagetian-based tests of conservation of length, measurement and the ability to identify Euclidean shapes. The students in the study were exposed to an expanded form of “Instant Logo” programming language using a guided discovery instructional approach. The training period lasted for six months. Posttest results indicated no significant differences between groups on all the measures, however the Logo teachers reported favorable impacts on the specific academic skills of left/right discrimination, knowledge of shape names, letter recognition and artwork. The results are discussed within a Piagetian framework and directions for future research are given.
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Robinson, Dylan. "Reparative interpellation: public art’s Indigenous and non-human publics." Journal of Visual Culture 21, no. 1 (2022): 69–84. http://dx.doi.org/10.1177/14704129221088299.
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This article considers the multiple ways in which public art interpellates viewers as settlers, Indigenous and non-human subjects. It could be argued that much public artwork in the late 20th and early 21st century has a ‘reparative’ function through its socially-engaged, community-specific and consciousness-raising aspects. To do so, however, would be to conflate the reparative with the recognition of injustice rather than understand it as the action of repair. The author asserts that for public art to engage in reparative work necessitates interrupting the normative forms and materialities of public art that interpellate the ‘public’ as settler subjects. How, he asks, might the reparative potential of public art be re-envisioned through a consideration of Indigenous and non-human publics?
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Cabezos-Bernal, Pedro M., Pablo Rodriguez-Navarro, and Teresa Gil-Piqueras. "Documenting Paintings with Gigapixel Photography." Journal of Imaging 7, no. 8 (2021): 156. http://dx.doi.org/10.3390/jimaging7080156.
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Digital photographic capture of pictorial artworks with gigapixel resolution (around 1000 megapixels or greater) is a novel technique that is beginning to be used by some important international museums as a means of documentation, analysis, and dissemination of their masterpieces. This line of research is extremely interesting, not only for art curators and scholars but also for the general public. The results can be disseminated through online virtual museum displays, offering a detailed interactive visualization. These virtual visualizations allow the viewer to delve into the artwork in such a way that it is possible to zoom in and observe those details, which would be negligible to the naked eye in a real visit. Therefore, this kind of virtual visualization using gigapixel images has become an essential tool to enhance cultural heritage and to make it accessible to everyone. Since today’s professional digital cameras provide images of around 40 megapixels, obtaining gigapixel images requires some special capture and editing techniques. This article describes a series of photographic methodologies and equipment, developed by the team of researchers, that have been put into practice to achieve a very high level of detail and chromatic fidelity, in the documentation and dissemination of pictorial artworks. The result of this research work consisted in the gigapixel documentation of several masterpieces of the Museo de Bellas Artes of Valencia, one of the main art galleries in Spain. The results will be disseminated through the Internet, as will be shown with some examples.