Relevant bibliographies by topics / Facial recognition

Academic literature on the topic 'Facial recognition'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 August 2024

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Facial recognition.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Facial recognition"

1

Goud, N. Swapna, K. Revanth Reddy, and G. Alekhya G. S. Sucheta. "Facial Emoji Recognition." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1330–33. http://dx.doi.org/10.31142/ijtsrd23166.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

C Karthik Srivatsa, Ashritha. "Facial Recognition Voting System (FRVS)." International Journal of Science and Research (IJSR) 12, no. 2 (February 5, 2023): 1144–46. http://dx.doi.org/10.21275/sr23217142716.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Deshwal, Amit, Mohnish Chandiramani, and Umesh Jagtap Prof Amruta Surana. "Smart Door Access using Facial Recognition." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (February 28, 2019): 442–43. http://dx.doi.org/10.31142/ijtsrd21363.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

a, Vinayak, and Rachana R. Babu. "Facial Emotion Recognition." YMER Digital 21, no. 05 (May 23, 2022): 1010–15. http://dx.doi.org/10.37896/ymer21.05/b5.

Full text
Abstract:
Human expresses their mood and sometimes what they need through their expression. This project traces the mood of the human using a real time recognition system which will detect the emotion. It can be a smiling face, or it can be the face full of anger. Facial emotion recognition is one of the useful task and can be used as a base for many real-time applications. The example can be feedback through moods at any restaurants and hotels about their services and foods. It can be much impactful in the field of military. Its very usage can be helpful for recognizing the people’s behaviour at the border areas to find out the suspects between them. This project consists of various algorithms of machine as well as deep learning. Some of the libraries are: Keras, OpenCV, Matplotlib. Image processing is used in classifying the universal emotions like neutral, surprise, sad, angry, happy, disguist, fear. This project consists of two modules: (i)Processing and generating the model for the application using different algorithms and (ii) Application for using the model using OpenCV to recognize. A set of values obtained after processing those extracted features points are given as input to recognize the emotion. Keywords: facial emotion recognition, deep neural networks, automatic recognition database
APA, Harvard, Vancouver, ISO, and other styles
5

Ramya, Mrs T., Mr Y. Anurag, Ms K. S. S. Pranathi, Mr M. Samba Raju, and Mr P. Rohith. "FACIAL EMOTION RECOGNITION." YMER Digital 21, no. 04 (April 29, 2022): 543–57. http://dx.doi.org/10.37896/ymer21.04/55.

Full text
Abstract:
Facial Emotion is the noticeable indication of the full of affective state, cognitive activity, intension, personality, and psychopathology of an individual and plays a communicative role in interpersonal relations. Automatic recognition of facial emotion can be a significant part of normal human-machine interfaces; it might likewise be utilized in conduct science and in clinical practice. An automatic Facial Emotion Recognition framework requirement to perform identification and area of countenances in a jumbled scene, facial component extraction, and look characterization. The facial emotion recognition framework is carried out utilizing the Deep Convolution Neural Network (DCNN). The CNN model of the undertaking depends on LeNet Architecture. Kaggle Facial Expression Dataset (FER-2013) with seven facial feelings named as happy, sad, surprise, fear, anger, disgust, and neutral is utilized in this venture. The framework accomplished 65% ± 5% accuracy.
APA, Harvard, Vancouver, ISO, and other styles
6

Hughes, Shola, Aimee Hudson, Sandra Jablonska, Matthew Wright, and Sophie Lawson. "Facial Recognition Technology." Student Journal of Professional Practice and Academic Research 3, no. 1 (March 4, 2021): 32. http://dx.doi.org/10.19164/sjppar.v3i1.1104.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Zuo, Kevin J., Tomas J. Saun, and Christopher R. Forrest. "Facial Recognition Technology." Plastic and Reconstructive Surgery 143, no. 6 (June 2019): 1298e—1306e. http://dx.doi.org/10.1097/prs.0000000000005673.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Benton, Arthur. "Facial Recognition 1990." Cortex 26, no. 4 (December 1990): 491–99. http://dx.doi.org/10.1016/s0010-9452(13)80299-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Maurya, Vikas, Ms Anjali Awasthi, Rajat Singh, Deepak Maurya, and Manorma Dwivedi. "Facial Emotion Recognition." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 4361–66. http://dx.doi.org/10.22214/ijraset.2023.51265.

Full text
Abstract:
Abstract: Facial emotion recognition (FER) has become an important topic in the fields of computer vision and artificial intelligence due to its great academic and commercial potential. Although FER can be performed using multiple sensors, this review focuses on studies using facial images exclusively, since visual expressions areone of the main channels of information in human communication. Automatic emotion recognition based onfacial expressions is an interesting research area that has been applied and applied in various fields such as safety, health and human-computer interface. Researchersin this field are interested in developing techniquesto interpret, encode facial expressions and extract these features for better prediction by computer. With the remarkable success of deep learning, different types of architectures of this technique are exploited to achieve better performance. The purpose of this paperisto conduct a study ofrecent work on automatic facial emotionrecognition (FER) via deep learning. We highlight these contributions, the architectures and the databases used, and we show the progress achieved by comparing the proposed methods and the obtained results. The purpose of this paper is to serve and guide researchers by reviewing recent work and providing insights to improve the field.
APA, Harvard, Vancouver, ISO, and other styles
10

Tiwari, Er Shesh Mani, and Er Mohd Shah Alam. "Facial Emotion Recognition." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (February 28, 2023): 490–94. http://dx.doi.org/10.22214/ijraset.2023.49067.

Full text
Abstract:
Abstract: Facial Emotion Recognition plays a significant role in interacting with computers which help us in various fields like medical processes, to present content on the basis of human mood, security and other fields. It is challenging because of heterogeneity in human faces, lighting, orientation, poses and noises. This paper aims to improve the accuracy of facial expression recognition. There has been much research done on the fer2013 dataset using CNN (Convolution Neural Network) and their results are quite impressive. In this work we performed CNN on the fer2013 dataset by adding images to improve the accuracy. To our best knowledge, our model achieves the accuracy of 70.23 % on fer2013 dataset after adding images in training and testing parts of disgusted class.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Facial recognition"

1

Boraston, Zillah Louise. "Emotion recognition from facial and non-facial cues." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1445207/.

Full text
Abstract:
The recognition of another's emotion is a vital component of social interaction, and a number of brain regions have been implicated in this process. This thesis describes a series of experiments which investigate further the neural basis of emotion recognition, and its disruption in autism, a disorder characterised by profound impairments in social and emotional understanding. First, I attempted to determine more precisely the role of two brain regions, the amygdala and fusiform gyrus, using multivariate analysis to investigate whether the identity of observed emotions is represented in the spatial pattern of activity in these regions. I next focused on a particular cue to emotion - that of social movement. For this purpose, I designed a novel test of emotion recognition using abstract animations. I used this in an fMRI study together with emotion recognition tasks relying on facial expression and prosody. I found that some brain regions involved in processing these more commonly studied cues were also recruited in emotion recognition from the animations. The final studies described here are concerned with emotion recognition in autism. I administered the social movement-based test of emotion recognition to adults with autism and found a deficit in sadness recognition, which extended to the recognition of sadness from facial expressions. Finally, I investigated the impact on emotion recognition of expertise with sensory cues, returning again to the processing of facial expressions. I employed a more subtle test of emotion processing, a posed smile discrimination task, and found impaired performance in the autism group and also reduced gaze to the eye region. These findings are discussed in view of current models of emotion recognition, with reference to the role of the amygdala and its interactions with specialised cortical regions, and the impact of early social experience on subsequent social perceptual and social cognitive ability.
APA, Harvard, Vancouver, ISO, and other styles
2

Sutherland, Kenneth Gavin Neil. "Automatic facial recognition based on facial feature analysis." Thesis, University of Edinburgh, 1992. http://hdl.handle.net/1842/13048.

Full text
Abstract:
As computerised storage and control of information is now a reality, it is increasingly necessary that personal identity verification be used as the automated method of access control to this information. Automatic facial recognition is now being viewed as an ideal solution to the problem of unobtrusive, high security, personal identity verification. However, few researchers have yet managed to produce a face recognition algorithm capable of performing successful recognition, without requiring substantial data storage for the personal information. This thesis reports the development of a feature and measurement based system of facial recognition, capable of storing the intrinsics of a facial image in a very small amount of data. The parameterisation of the face into its component characteristics is essential to both human and automated face recognition. Psychological and behavioural research has been reviewed in this thesis in an attempt to establish any key pointers, in human recognition, which can be exploited for use in an automated system. A number of different methods of automated facial recognition which perform facial parameterisation in a variety of different ways are discussed. In order to store the relevant characteristics and measurements about the face, the pertinent facial features must be precisely located from within the image data. A novel technique of Limited Feature Embedding, which locates the primary facial features with a minimum of computational load, has been successfully designed and implemented. The location process has been extended to isolate a number of other facial features. With regard to the earlier review, a new method of facial parameterisation has been devised. Incorporated in this feature set are local feature data and structural measurement information about the face. A probabilistic method of inter-person comparisons which facilitates recognition even in the presence of expressional and temporal changes, has been successfully implemented. Comprehensive results of this novel recognition technique are presented for a variety of different operating conditions.
APA, Harvard, Vancouver, ISO, and other styles
3

Munasinghe, Kankanamge Sarasi Madushika. "Facial analysis models for face and facial expression recognition." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/118197/1/Sarasi%20Madushika_Munasinghe%20Kankanamge_Thesis.pdf.

Full text
Abstract:
This thesis examines the research and development of new approaches for face and facial expression recognition within the fields of computer vision and biometrics. Expression variation is a challenging issue in current face recognition systems and current approaches are not capable of recognizing facial variations effectively within human-computer interfaces, security and access control applications. This thesis presents new contributions for performing face and expression recognition simultaneously; face recognition in the wild; and facial expression recognition in challenging environments. The research findings include the development of new factor analysis and deep learning approaches which can better handle different facial variations.
APA, Harvard, Vancouver, ISO, and other styles
4

Bordon, Natalie Sarah. "Facial affect recognition in psychosis." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22865.

Full text
Abstract:
While a correlation between suffering from psychosis and an increased risk of engaging in aggressive behaviours has been established, many factors have been explored which may contribute to increasing this risk. Patients with a diagnosis of psychosis have been shown to have significant difficulties in facial affect recognition (FAR) and some authors have proposed that this may contribute to increasing the risk of displaying aggressive or violent behaviours. A systematic review of the current evidence regarding the links between facial affect recognition and aggression was conducted. Results were varied with some studies providing evidence of a link between emotion recognition difficulties and aggression, while others were unable to establish such an association. Results should be interpreted with some caution as the quality of included studies was poor due to small sample sizes, insufficient power and limited reporting of results. Adequately powered, randomised controlled studies using appropriate blinding procedures and validated measures are therefore required. There is a substantial evidence base demonstrating difficulties in emotional perception in patients with psychosis, with evidence suggesting a relationship with reduced social functioning, increased aggression and more severe symptoms of psychosis. In this review we aim to review this field to assess if there is a causal link between facial affect recognition difficulties and psychosis. The Bradford Hill criteria for establishing a causal relationship from observational data were used to generate key hypotheses, which were then tested against existing evidence. Where a published meta-analysis was not already available, new meta-analyses were conducted. A large effect of FAR difficulties in those with a diagnosis of psychosis, with a small to moderate correlation between FAR problems and symptoms of psychosis was found. Evidence was provided for the existence of FAR problems in those at clinical high risk of psychosis, while remediation of psychosis symptoms did not appear to impact FAR difficulties. There appears to be good evidence of the existence of facial affect recognition difficulties in the causation of psychosis, though larger, longitudinal studies are required to provide further evidence of this.
APA, Harvard, Vancouver, ISO, and other styles
5

Huang, Weilin. "Robust facial representation for recognition." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/robust-facial-representation-for-recognition(ee2f295c-7b1a-4966-bd12-17edba43b2b4).html.

Full text
Abstract:
One of the main challenges in face recognition lies in robust representation of facial images in unconstrained real-world environment, where face appearances of a same person often vary significantly. This thesis investigates both holistic and local feature based representations, and develops several novel representation models in an effort to mitigate within-person variations and enhance discriminative power.The work first focuses on feature extraction of high-dimensional holistic representation based on intensities. Several linear and nonlinear dimensionality reduction methods are systematically compared. One of key findings is that linear PCA has comparable performances to the most recent nonlinear methods for extracting low-dimensional facial features. Extensive experiments are conducted and results are presented to support the findings, together with a quantitative measure of nonlinearity showing theoretical insights. Following these findings, a robust framework combining an automatic outlier detector and a nearest subspace classifier, is presented. The detector computes the corrupted regions of face images by measuring their reconstructive capabilities, while the classifier models face data by multiple linear subspaces.
APA, Harvard, Vancouver, ISO, and other styles
6

Yu, Kaimin. "Towards Realistic Facial Expression Recognition." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9459.

Full text
Abstract:
Automatic facial expression recognition has attracted significant attention over the past decades. Although substantial progress has been achieved for certain scenarios (such as frontal faces in strictly controlled laboratory settings), accurate recognition of facial expression in realistic environments remains unsolved for the most part. The main objective of this thesis is to investigate facial expression recognition in unconstrained environments. As one major problem faced by the literature is the lack of realistic training and testing data, this thesis presents a web search based framework to collect realistic facial expression dataset from the Web. By adopting an active learning based method to remove noisy images from text based image search results, the proposed approach minimizes the human efforts during the dataset construction and maximizes the scalability for future research. Various novel facial expression features are then proposed to address the challenges imposed by the newly collected dataset. Finally, a spectral embedding based feature fusion framework is presented to combine the proposed facial expression features to form a more descriptive representation. This thesis also systematically investigates how the number of frames of a facial expression sequence can affect the performance of facial expression recognition algorithms, since facial expression sequences may be captured under different frame rates in realistic scenarios. A facial expression keyframe selection method is proposed based on keypoint based frame representation. Comprehensive experiments have been performed to demonstrate the effectiveness of the presented methods.
APA, Harvard, Vancouver, ISO, and other styles
7

Sheikh, Munaf. "Robust recognition of facial expressions on noise degraded facial images." Thesis, University of the Western Cape, 2011. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_7054_1306828003.

Full text
Abstract:

We investigate the use of noise degraded facial images in the application of facial expression recognition. In particular, we trained Gabor+SVMclassifiers to recognize facial expressions images with various types of noise. We applied Gaussian noise, Poisson noise, varying levels of salt and pepper noise, and speckle noise to noiseless facial images. Classifiers were trained with images without noise and then tested on the images with noise. Next, the classifiers were trained using images with noise, and then on tested both images that had noise, and images that were noiseless. Finally, classifiers were tested on images while increasing the levels of salt and pepper in the test set. Our results reflected distinct degradation of recognition accuracy. We also discovered that certain types of noise, particularly Gaussian and Poisson noise, boost recognition rates to levels greater than would be achieved by normal, noiseless images. We attribute this effect to the Gaussian envelope component of Gabor filters being sympathetic to Gaussian-like noise, which is similar in variance to that of the Gabor filters. Finally, using linear regression, we mapped a mathematical model to this degradation and used it to suggest how recognition rates would degrade further should more noise be added to the images.

APA, Harvard, Vancouver, ISO, and other styles
8

de, la Cruz Nathan. "Autonomous facial expression recognition using the facial action coding system." University of the Western Cape, 2016. http://hdl.handle.net/11394/5121.

Full text
Abstract:
>Magister Scientiae - MSc
The South African Sign Language research group at the University of the Western Cape is in the process of creating a fully-edged machine translation system to automatically translate between South African Sign Language and English. A major component of the system is the ability to accurately recognise facial expressions, which are used to convey emphasis, tone and mood within South African Sign Language sentences. Traditionally, facial expression recognition research has taken one of two paths: either recognising whole facial expressions of which there are six i.e. anger, disgust, fear, happiness, sadness, surprise, as well as the neutral expression; or recognising the fundamental components of facial expressions as defined by the Facial Action Coding System in the form of Action Units. Action Units are directly related to the motion of specific muscles in the face, combinations of which are used to form any facial expression. This research investigates enhanced recognition of whole facial expressions by means of a hybrid approach that combines traditional whole facial expression recognition with Action Unit recognition to achieve an enhanced classification approach.
APA, Harvard, Vancouver, ISO, and other styles
9

Fraser, Matthew Paul. "Repetition priming of facial expression recognition." Thesis, University of York, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431255.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Hsu, Shen-Mou. "Adaptation effects in facial expression recognition." Thesis, University of York, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403968.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Facial recognition"

1

Young, A. W. Facial Expression Recognition. London ; New York : Psychology Press, 2016. | Series: World: Psychology Press, 2016. http://dx.doi.org/10.4324/9781315715933.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Watkins, Elizabeth Anne. The Polysemia of Recognition: Facial Recognition in Algorithmic Management. [New York, N.Y.?]: [publisher not identified], 2021.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Jr, Woodward John D., Virginia State Crime Commission, and Rand Corporation, eds. Biometrics: A look at facial recognition. Santa Monica, Calif: RAND, 2003.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bai, Xiang, Yi Fang, Yangqing Jia, Meina Kan, Shiguang Shan, Chunhua Shen, Jingdong Wang, et al., eds. Video Analytics. Face and Facial Expression Recognition. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12177-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Evison, Martin Paul. Computer-aided forensic facial comparison. Boca Raton, FL: Taylor & Francis Group, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

W, Vorder Bruegge Richard, ed. Computer-aided forensic facial comparison. Boca Raton, FL: Taylor & Francis Group, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Ji, Qiang, Thomas B. Moeslund, Gang Hua, and Kamal Nasrollahi, eds. Face and Facial Expression Recognition from Real World Videos. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13737-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Nasrollahi, Kamal, Cosimo Distante, Gang Hua, Andrea Cavallaro, Thomas B. Moeslund, Sebastiano Battiato, and Qiang Ji, eds. Video Analytics. Face and Facial Expression Recognition and Audience Measurement. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56687-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Diminich, Erica. Is this the face of sadness? Facial expression recognition and context. [New York, N.Y.?]: [publisher not identified], 2015.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Michela, Balconi, ed. Neuropsychology and cognition of emotional face comprehension, 2006. Trivandrum, India: Research Signpost, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Facial recognition"

1

Pennick, Mark. "Facial Recognition." In Encyclopedia of Child Behavior and Development, 634. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-79061-9_1087.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Smith, Marcus, Monique Mann, and Gregor Urbas. "Facial recognition." In Biometrics, Crime and Security, 54–70. New York : Routledge, 2018. | Series: Law, science and society: Routledge, 2018. http://dx.doi.org/10.4324/9781315182056-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Das, Ravindra. "Facial Recognition." In The Science of Biometrics, 179–268. New York, NY : Routledge, 2018. |: Routledge, 2018. http://dx.doi.org/10.4324/9780429487583-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Lawless, Christopher. "Facial recognition." In Forensic Science, 111–24. 2nd ed. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003126379-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Lin, Yuchen, Zhehen Zheng, and Yang Zhou. "Facial Recognition." In Information Technology Security and Risk Management, 193–211. New York: CRC Press, 2024. http://dx.doi.org/10.1201/9781003264415-30.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Perkowitz, Sidney. "Facing up to Facial Recognition." In Science Sketches, 257–59. New York: Jenny Stanford Publishing, 2022. http://dx.doi.org/10.1201/9781003274964-51.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Jiang, Xiaoyi, and Yung-Fu Chen. "Facial Image Processing." In Applied Pattern Recognition, 29–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-76831-9_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Clark, Uraina. "Facial Recognition Test." In Encyclopedia of Clinical Neuropsychology, 1010–12. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1364.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Clark, Uraina. "Facial Recognition Test." In Encyclopedia of Clinical Neuropsychology, 1–3. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1364-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Sebe, Nicu, and Michael S. Lew. "Facial Expression Recognition." In Computational Imaging and Vision, 163–97. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0295-9_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Facial recognition"

1

Park, Sungsoo, and Daijin Kim. "Spontaneous facial expression classification with facial motion vectors." In Gesture Recognition (FG). IEEE, 2008. http://dx.doi.org/10.1109/afgr.2008.4813308.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Huang, Yanhui, Xing Zhang, Yangyu Fan, Lijun Yin, Lee Seversky, Tao Lei, and Weijun Dong. "Reshaping 3D facial scans for facial appearance modeling and 3D facial expression analysis." In Gesture Recognition (FG 2011). IEEE, 2011. http://dx.doi.org/10.1109/fg.2011.5771436.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Xiaoxi, Ma, Lin Weisi, Huang Dongyan, Dong Minghui, and Haizhou Li. "Facial emotion recognition." In 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP). IEEE, 2017. http://dx.doi.org/10.1109/siprocess.2017.8124509.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Reveriano, Francisco, Unal Sakoglu, and Jiang Lu. "Facial Expression Recognition." In PEARC '19: Practice and Experience in Advanced Research Computing. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3332186.3333039.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Roundtree, Aimee. "Facial Recognition UX*." In SIGDOC '21: The 39th ACM International Conference on Design of Communication. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3472714.3473647.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kulkarni, Ketki R., and Sahebrao B. Bagal. "Facial expression recognition." In 2015 International Conference on Information Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/infop.2015.7489442.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Kaur, Japleen, Jhalak Saxena, Jayesh Shah, Fahad, and Satya Prakash Yadav. "Facial Emotion Recognition." In 2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES). IEEE, 2022. http://dx.doi.org/10.1109/cises54857.2022.9844366.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Slimani, K., M. Kas, Y. El Merabet, R. Messoussi, and Y. Ruichek. "Facial emotion recognition." In the 2nd Mediterranean Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3177148.3180092.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Kulkarni, Ketki R., and Sahebrao B. Bagal. "Facial Expression Recognition." In 2015 Annual IEEE India Conference (INDICON). IEEE, 2015. http://dx.doi.org/10.1109/indicon.2015.7443572.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Melaugh, Ryan, Nazmul Siddique, Sonya Coleman, and Pratheepan Yogarajah. "Facial Expression Recognition on partial facial sections." In 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA). IEEE, 2019. http://dx.doi.org/10.1109/ispa.2019.8868630.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Facial recognition"

1

Kroll, Joshua A. ACM TechBrief: Facial Recognition Technology. ACM, February 2022. http://dx.doi.org/10.1145/3520137.

Full text
Abstract:
Facial recognition is not a monolithic technology or a particular technique. Rather, facial recognition refers to any technology that automatically processes and purports to identify faces in images or videos. While humans interpret faces easily, computers must extract patterns from data or humans must code patterns into the system. Applying these patterns yields the facial descriptors (often referred to as faceprints) on which facial recognition systems rely to achieve their function.
APA, Harvard, Vancouver, ISO, and other styles
2

Eastman, Brittany. Legal Issues Facing Automated Vehicles, Facial Recognition, and Privacy Rights. SAE International, July 2022. http://dx.doi.org/10.4271/epr2022016.

Full text
Abstract:
Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality. Legal Issues Facing Automated Vehicles, Facial Recognition, and Individual Rights seeks to highlight the benefits of using FRS in public and private transportation technology and addresses some of the legitimate concerns regarding its use by private corporations and government entities, including law enforcement, in public transportation hubs and traffic stops. Constitutional questions, including First, Forth, and Ninth Amendment issues, also remain unanswered. FRS is now a permanent part of transportation technology and society; with meaningful legislation and conscious engineering, it can make future transportation safer and more convenient.
APA, Harvard, Vancouver, ISO, and other styles
3

Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.

Full text
Abstract:
Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmarks, while others bring out more detail. We use 68 facial markup, which is a common format for many datasets. Cloud computing creates all the necessary conditions for the successful implementation of even the most complex tasks. We created a web application using the Django framework, Python language, OpenCv and Dlib libraries to recognize faces in the image. The purpose of our work is to create a software system for face recognition in the photo and identify wrinkles on the face. The algorithm for determining the presence and location of various types of wrinkles and determining their geometric determination on the face is programmed.
APA, Harvard, Vancouver, ISO, and other styles
4

Cain, R. A., and G. B. Singleton. Laptop Computer - Based Facial Recognition System Assessment. Office of Scientific and Technical Information (OSTI), March 2001. http://dx.doi.org/10.2172/780800.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Mitchell, Michael. Facial Recognition Training: Improving Intelligence Collection by Soldiers. Fort Belvoir, VA: Defense Technical Information Center, January 2008. http://dx.doi.org/10.21236/ada494904.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kimura, Marcia L., Rebecca L. Erikson, and Nicholas J. Lombardo. Non-Cooperative Facial Recognition Video Dataset Collection Plan. Office of Scientific and Technical Information (OSTI), August 2013. http://dx.doi.org/10.2172/1126360.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Eastman, Brittany. Facial Recognition Software and Privacy Law in Transportation Technology. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, May 2024. http://dx.doi.org/10.4271/epr2024011.

Full text
Abstract:
<div class="section abstract"><div class="htmlview paragraph">Data privacy questions are particularly timely in the automotive industry as—now more than ever before—vehicles are collecting and sharing data at great speeds and quantities. Though connectivity and vehicle-to-vehicle technologies are perhaps the most obvious, smart city infrastructure, maintenance, and infotainment systems are also relevant in the data privacy law discourse.</div><div class="htmlview paragraph"><b>Facial Recognition Software and Privacy Law in Transportation Technology</b> considers the current legal landscape of privacy law and the unanswered questions that have surfaced in recent years. A survey of the limited recent federal case law and statutory law, as well as examples of comprehensive state data privacy laws, is included. Perhaps most importantly, this report simplifies the balancing act that manufacturers and consumers are performing by complying with data privacy laws, sharing enough data to maximize safety and convenience, and protecting personal information.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
APA, Harvard, Vancouver, ISO, and other styles
8

Segar, Gabrielle. The Unethical Nature of Artificial Intelligence within Facial Recognition Technologies. Ames (Iowa): Iowa State University, May 2024. http://dx.doi.org/10.31274/cc-20240624-1498.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bromberg, Daniel, Étienne Charbonneau, and Andrew Smith. Facial Recognition and Drivers’ Licenses: Should the DMV Share Your Photo? University of New Hampshire Libraries, 2019. http://dx.doi.org/10.34051/p/2020.366.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Selinger, Andrea, and Diego A. Socolinsky. Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A Comparative Study. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada444419.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Facial recognition' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography