Relevant bibliographies by topics / Vision; Point of view

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Vision; Point of view'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Vision; Point of view"

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VON BONHORST, C. "European vision research - An independent point of view." Acta Ophthalmologica 86 (September 4, 2008): 0. http://dx.doi.org/10.1111/j.1755-3768.2008.4211.x.

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Brown, Alan S. "The New Point of View." Mechanical Engineering 130, no. 02 (February 1, 2008): 22–27. http://dx.doi.org/10.1115/1.2008-feb-1.

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This paper emphasizes on various aspects of human factors engineering. Researchers believe that superior design creates demand for new products. According to a human factor engineer, a design succeeds because it improves the user’s experience, defined in this case as time to complete a procedure. Metaphase Design’s new paintbrush for Shur-Line looks cool and uses human factors research to improve control and reduce forearm stress. Studies show that a parent’s voice wakes children better than an alarm during a fire. Hospitals and clinicians will pay a premium so they can work faster and more efficiently. Today, a growing number of designers have embraced human factors techniques, while extending those techniques to include emotion and cognition to shape the experience of the user. There is a need for a powerful user experience along with good looks for a product to be successful. The paper concludes that despite all the emphasis on human factors, personality and product profiling, and collaboration, the thinking behind it remains a very human and very personal vision.
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Xu, Zheng Guang, Chen Chen, and Xu Hong Liu. "An Efficient View-Point Invariant Detector and Descriptor." Advanced Materials Research 659 (January 2013): 143–48. http://dx.doi.org/10.4028/www.scientific.net/amr.659.143.

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Many computer vision applications need keypoint correspondence between images under different view conditions. Generally speaking, traditional algorithms target applications with either good performance in invariance to affine transformation or speed of computation. Nowadays, the widely usage of computer vision algorithms on handle devices such as mobile phones and embedded devices with low memory and computation capability has proposed a target of making descriptors faster to computer and more compact while remaining robust to affine transformation and noise. To best address the whole process, this paper covers keypoint detection, description and matching. Binary descriptors are computed by comparing the intensities of two sampling points in image patches and they are matched by Hamming distance using an SSE 4.2 optimized popcount. In experiment results, we will show that our algorithm is fast to compute with lower memory usage and invariant to view-point change, blur change, brightness change, and JPEG compression.
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Elliott, Portia. "One Point of View: Reclaiming School Mathematics." Arithmetic Teacher 37, no. 8 (April 1990): 4–5. http://dx.doi.org/10.5951/at.37.8.0004.

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The framers of the Curriculum and Evaluation Standards for School Mathematics (NCTM 1989) call for a radical “design change” in all aspects of mathematics education. They believe that “evaluation is a tool for implementing the Standards and effecting change systematically” (p. 189). They warn, however, that “without changes in how mathematics is assessed, the vision of the mathematics curriculum described in the standards will not be implemented in classrooms, regardless of how texts or local curricula change” (p. 252).
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Bogdănici, Camelia-Margareta, Ştefan Tudor Bogdănici, Diana Elena Săndulache, and Carmen-Mariana Diaconu. "Medical and legal point of view for low-vision patients." Romanian Journal of Ophthalmology 62, no. 1 (April 19, 2018): 48–53. http://dx.doi.org/10.22336/rjo.2018.7.

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KATO, Hisatake. "Brave new vision of freedom from environmentethical point of view." Journal of the Atomic Energy Society of Japan / Atomic Energy Society of Japan 32, no. 8 (1990): 760–64. http://dx.doi.org/10.3327/jaesj.32.760.

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MIZUMOTO, Hiroshi, Yoshito YABUTA, Hironori KOBAYASHI, and Shiro ARII. "A Binocular Machine Vision System using an Active View Point." Journal of the Japan Society for Precision Engineering 62, no. 10 (1996): 1434–38. http://dx.doi.org/10.2493/jjspe.62.1434.

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Aksın Artok, Özge, Michael Schiller, and Mark Everard. "Metal soaps under the view point of sustainability-One vision." Journal of Vinyl and Additive Technology 23, no. 2 (June 11, 2015): 125–34. http://dx.doi.org/10.1002/vnl.21487.

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Asadollahi, Zahra, and Vola M. Andrianarijaona. "Eye Accommodation, Near Vision, and Far Vision from a Geometrical Optics Point of View." Physics Teacher 59, no. 6 (September 2021): 417–19. http://dx.doi.org/10.1119/10.0006116.

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CHENG, JIN-CHANG, and HON-SON DON. "A GRAPH MATCHING APPROACH TO 3-D POINT CORRESPONDENCES." International Journal of Pattern Recognition and Artificial Intelligence 05, no. 03 (August 1991): 399–412. http://dx.doi.org/10.1142/s0218001491000223.

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A recursive descent tree traversal algorithm is presented to find the point correspondences between two views. Given two sets of noisy 3-D feature points on multiple rigid objects at two time-sequential views, the points at the first view are constructed as a graph and then another graph is derived from those feature points at the second view so that a maximal matching point and minimum matching error is obtained. The correspondence of the vertices is then found. The algorithm can also he used when the number of points at two views are different. Therefore, after matching, the occluded points at either view or both views can be identified. The computation time of the proposed algorithm is large when the number of feature points is large. A data set splitting strategy for such cases, which can significantly reduce the computation time, is presented. Another algorithm presented is one in which motion parameters are estimated from a matched subgraph and are then used to guide the matching for the rest of the nodes. Computer simulations are performed to show the efficiency and accuracy of the algorithm.
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Dissertations / Theses on the topic "Vision; Point of view"

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Israel, Lana. "Memory perspective and recollective experience." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365442.

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Diskin, Yakov. "Dense 3D Point Cloud Representation of a Scene Using Uncalibrated Monocular Vision." University of Dayton / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1366386933.

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Alturki, Abdulrahman S. "Principal Point Determination for Camera Calibration." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1500326474390507.

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Graehling, Quinn R. "Feature Extraction Based Iterative Closest Point Registration for Large Scale Aerial LiDAR Point Clouds." University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1607380713807017.

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Roesler, Axel. "A new model for perspective the role of point of observation in virtual and remote perspective-taking /." Columbus, Ohio : Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1133297173.

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Stein, Madeleine. "Improving Image Based Fruitcount Estimates Using Multiple View-Points." Thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-132402.

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This master-thesis presents an approach to track and count the number of fruit incommercial mango orchards. The algorithm is intended to enable precision agri-culture and to facilitate labour and post-harvest storage planning. The primary objective is to develop an multi-view algorithm and investigate how it can beused to mitigate the effects of visual occlusion, to improve upon estimates frommethods that use a single central or two opposite viewpoints. Fruit are detectedin images by using two classification methods: dense pixel-wise cnn and regionbased r-cnn detection. Pair-wise fruit correspondences are established between images by using geometry provided by navigation data, and lidar data is used to generate image masks for each separate tree, to isolate fruit counts to individual trees. The tracked fruit are triangulated to locate them in 3D space, and spatial statistics are calculated over whole orchard blocks. The estimated tree counts are compared to single view estimates and validated against ground truth data of 16 mango trees from a Bundaberg mango orchard in Queensland, Australia. The results show a high R2-value of 0.99335 for four hand labelled trees and a highest R2-value of 0.9165 for the machine labelled images using the r-cnn classifier forthe 16 target trees.
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Feydt, Austin Pack. "A Higher-Fidelity Approach to Bridging the Simulation-Reality Gap for 3-D Object Classification." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1558355175360648.

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Bharadwaj, Akshay S. "A Perception Payload for Small-UAS Navigation in Structured Environments." Ohio University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1533649419108963.

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Fu, Wenhao. "Visual servoing for mobile robots navigation with collision avoidance and field-of-view constraints." Thesis, Evry-Val d'Essonne, 2014. http://www.theses.fr/2014EVRY0019/document.

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Cette thèse porte sur le problème de la navigation basée sur la vision pour les robots mobiles dans les environnements intérieurs. Plus récemment, de nombreux travaux ont été réalisés pour résoudre la navigation à l'aide d'un chemin visuel, à savoir la navigation basée sur l'apparence. Cependant, en utilisant ce schéma, le mouvement du robot est limité au chemin visuel d'entrainement. Le risque de collision pendant le processus de navigation peut faire écarter le robot de la trajectoire visuelle courante, pour laquelle les repères visuels peuvent être perdus. Dans l'état de nos connaissances, les travaux envisagent rarement l'évitement des collisions et la perte de repère dans le cadre de la navigation basée sur l'apparence. Nous présentons un cadre mobile de navigation pour le robot afin de renforcer la capacité de la méthode basée sur l'apparence, notamment en cas d'évitement de collision et de contraintes de champ de vision. Notre cadre introduit plusieurs contributions techniques. Tout d'abord, les contraintes de mouvement sont considérés dans la détection de repère visuel pour améliorer la performance de détection. Ensuite, nous modélisons l'obstacle en utilisant B-Spline. La représentation de B-Spline n'a pas de régions accidentées et peut générer un mouvement fluide pour la tâche d'évitement de collision. En outre, nous proposons une stratégie de contrôle basée sur la vision, qui peut gérer la perte complète de la cible. Enfin, nous utilisons l'image sphérique pour traiter le cas des projections d'ambiguité et d'infini dus à la projection en perspective. Les véritables expériences démontrent la faisabilité et l'efficacité de notre cadre et de nos méthodes
This thesis is concerned with the problem of vision-based navigation for mobile robots in indoor environments. Many works have been carried out to solve the navigation using a visual path, namely appearance-based navigation. However, using this scheme, the robot motion is limited to the trained visual path. The potential collision during the navigation process can make robot deviate from the current visual path, in which the visual landmarks can be lost in the current field of view. To the best of our knowledge, seldom works consider collision avoidance and landmark loss in the framework of appearance-based navigation. We outline a mobile robot navigation framework in order to enhance the capability of appearance-based method, especially in case of collision avoidance and field-of-view constraints. Our framework introduces several technical contributions. First of all, the motion constraints are considered into the visual landmark detection to improve the detection performance. Next then, we model the obstacle boundary using B-Spline. The B-Spline representation has no accidented regions and can generate a smooth motion for the collision avoidance task. Additionally, we propose a vision-based control strategy, which can deal with the complete target loss. Finally, we use spherical image to handle the case of ambiguity and infinity projections due to perspective projection. The real experiments demonstrate the feasability and the effectiveness of our framework and methods
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Aganj, Ehsan. "Multi-view Reconstruction and Texturing=Reconstruction multi-vues et texturation." Phd thesis, Ecole des Ponts ParisTech, 2009. http://pastel.archives-ouvertes.fr/pastel-00517742.

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Dans cette thèse, nous étudions les problèmes de reconstruction statique et dynamique à partir de vues multiples et texturation, en s'appuyant sur des applications réelles et pratiques. Nous proposons trois méthodes de reconstruction destinées à l'estimation d'une représentation d'une scène statique/dynamique à partir d'un ensemble d'images/vidéos. Nous considérons ensuite le problème de texturation multi-vues en se concentrant sur la qualité visuelle de rendu..
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Books on the topic "Vision; Point of view"

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Ark, Laurine. Writing from the exterior dramatic perspective: A new vision for literature. New York: Fort Tryon Press, 1996.

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Vision voiced: Narrative viewpoint in autobiographical writing. New York: P. Lang, 1991.

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Thorne, Alison. Vision and rhetoric in Shakespeare: Looking through language. New York: St. Martin's Press, 2000.

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Point of view. Oakland, Calif: Regent Press, 2004.

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Preston, Rick. Point of view. New York: A. van der Marck Editions, 1989.

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Levi, Edward H. Point of View. Chicago: University of Chicago Press, 2008.

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1957-, Høeg Peter, ed. Point of view. New York, NY: Aperture, 1998.

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Bijarani, M. H. K. Point of view. Rawalpindi: Foundation for Research on International Environment, National Development and Security (FRIENDS), 1998.

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Decker, Simone. Point of view. Luxembourg: Casino Luxembourg, 2005.

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Kalim, Mazhar. Large view point. Multan: Yusaf Brothers, 2002.

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Book chapters on the topic "Vision; Point of view"

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Nozawa, Kazuki, Akihiko Torii, and Masatoshi Okutomi. "Stable Two View Reconstruction Using the Six-Point Algorithm." In Computer Vision – ACCV 2012, 122–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37447-0_10.

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Song, Zhenbo, Wayne Chen, Dylan Campbell, and Hongdong Li. "Deep Novel View Synthesis from Colored 3D Point Clouds." In Computer Vision – ECCV 2020, 1–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58586-0_1.

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Du, Jia, Wei Xiong, Wenyu Chen, Jierong Cheng, Yue Wang, Ying Gu, and Shue-Ching Chia. "Multi-view Point Cloud Registration Using Affine Shape Distributions." In Computer Vision -- ACCV 2014, 147–61. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16808-1_11.

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Da Fonseca, José Luís S., José Barahona da Fonseca, and Isabel Barahona da Fonseca. "Vision–An Essay from a Computational View Point." In Computer Aided Systems Theory - EUROCAST 2009, 143–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04772-5_20.

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Zhou, Lei, Siyu Zhu, Zixin Luo, Tianwei Shen, Runze Zhang, Mingmin Zhen, Tian Fang, and Long Quan. "Learning and Matching Multi-View Descriptors for Registration of Point Clouds." In Computer Vision – ECCV 2018, 527–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01267-0_31.

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Chen, Tingwang, and Qing Wang. "3D Line Segment Detection for Unorganized Point Clouds from Multi-view Stereo." In Computer Vision – ACCV 2010, 400–411. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19309-5_31.

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Li, Hongdong. "A Simple Solution to the Six-Point Two-View Focal-Length Problem." In Computer Vision – ECCV 2006, 200–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11744085_16.

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Zheng, Hanfeng, Huijun Di, Yaohang Han, and Jianwei Gong. "TriSpaSurf: A Triple-View Outline Guided 3D Surface Reconstruction of Vehicles from Sparse Point Cloud." In Pattern Recognition and Computer Vision, 398–409. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60633-6_33.

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Ma, Yi, Stefano Soatto, Jana Košecká, and S. Shankar Sastry. "Multiple-View Geometry of Points and Lines." In An Invitation to 3-D Vision, 263–309. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-0-387-21779-6_8.

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Haag, Michael, and Hans Hellmut Nagel. "Beginning a transition from a local to a more global point of view in model-based vehicle tracking." In Computer Vision — ECCV'98, 812–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055706.

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Conference papers on the topic "Vision; Point of view"

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Cunnington, S. J., and A. Stoddart. "N-View Point Set Registration: A Comparison." In British Machine Vision Conference 1999. British Machine Vision Association, 1999. http://dx.doi.org/10.5244/c.13.24.

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"FREE-VIEW POINT TV WATERMARKING EVALUATED ON GENERATED ARBITRARY VIEWS." In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001084201460151.

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Chen, Rui, Songfang Han, Jing Xu, and Hao Su. "Point-Based Multi-View Stereo Network." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00162.

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Bettadapura, Vinay, Irfan Essa, and Caroline Pantofaru. "Egocentric Field-of-View Localization Using First-Person Point-of-View Devices." In 2015 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2015. http://dx.doi.org/10.1109/wacv.2015.89.

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Motiur Rahaman, D. M., and Manoranjan Paul. "Free view-point video synthesis using Gaussian Mixture Modelling." In 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2015. http://dx.doi.org/10.1109/ivcnz.2015.7761513.

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Pang, Guan, and Ulrich Neumann. "Fast and Robust Multi-view 3D Object Recognition in Point Clouds." In 2015 International Conference on 3D Vision (3DV). IEEE, 2015. http://dx.doi.org/10.1109/3dv.2015.27.

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Duff, Timothy, Kathlen Kohn, Anton Leykin, and Tomas Pajdla. "PLMP - Point-Line Minimal Problems in Complete Multi-View Visibility." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00176.

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Mieloch, David, Dominika Klóska, and Magdalena Woźniak. "Point-to-Block Matching in Depth Estimation." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita, 2021. http://dx.doi.org/10.24132/csrn.2021.3002.15.

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In this paper, the novel correspondence search method called point-to-block matching was proposed. Recently, in many proposed multimedia systems, depth estimation is performed on compressed input views. To address this problem and increase the quality of such depth maps, in the proposal, a point in a view is not compared simply with a point in another view, but to the most similar point in a small block surrounding it. The introduction of this method in the depth estimation process is beneficial to the quality of depth maps, as it decreases the influence of small shifts in images, caused e.g., by encoding-related errors introduced to input views. The method was implemented in one of the state-of-the-art depth estimation methods and tested in series of experiments. Based on the comparison of synthesized virtual views with the input views, the proposal increases the quality of estimated depth maps in most of the tested configurations.
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Sedaghat, Nima, and Thomas Brox. "Unsupervised Generation of a View Point Annotated Car Dataset from Videos." In 2015 IEEE International Conference on Computer Vision (ICCV). IEEE, 2015. http://dx.doi.org/10.1109/iccv.2015.155.

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Bobkov, Dmytro, Sili Chen, Martin Kiechle, Sebastian Hilsenbeck, and Eckehard Steinbach. "Noise-resistant Unsupervised Object Segmentation in Multi-view Indoor Point Clouds." In International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006100801490156.

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Reports on the topic "Vision; Point of view"

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Busta, Heinz H. MEMS Direct View Infrared Vision System (DVIR). Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada388262.

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Milanich, A. Classical point of view on the photon. SIS journal, 2018. http://dx.doi.org/10.18411/201-8-p68.

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Marasco, Peter L., and H. L. Task. Optical Characterization of Wide Field-of-View Night Vision Devices. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada430272.

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Ikawa, Osamu. Motion of Charged Particles From the Geometric View Point. Journal of Geometry and Symmetry in Physics, 2012. http://dx.doi.org/10.7546/jgsp-18-2010-23-47.

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Sullivan, P. Vision d'avenir : le point de vue d'un arpenteur général. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/300272.

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Greenstein, Shane, and Feng Zhu. Collective Intelligence and Neutral Point of View: The Case of Wikipedia. Cambridge, MA: National Bureau of Economic Research, June 2012. http://dx.doi.org/10.3386/w18167.

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Z. Bajnok. Symplectic Leaves of W-Algebras from the Reduced Kac–Moody Point of View. GIQ, 2012. http://dx.doi.org/10.7546/giq-2-2001-99-109.

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Garipova, Z. F. ATTRACTIVENESS OF THE TERRITORY FROM THE POINT OF VIEW OF ACCOMMODATION WORK FORCE. Bulletin of Eurasian Science, 2019. http://dx.doi.org/10.18411/elibrary-38553254-53542611.

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Smyth, Christopher C., James W. Gombash, and Patricia M. Burcham. Indirect Vision Driving with Fixed Flat Panel Displays for Near Unity, Wide, and Extended Fields of Camera View. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada395211.

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Geri, George A., Paul A. Wetzel, and Elizabeth L. Martin. Head and Eye Movements in Free Visual Search: Effects of Restricted Field of View and Night Vision Goggle Imagery. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada379370.

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