Academic literature on the topic 'Perception of Occlusion'
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Journal articles on the topic "Perception of Occlusion"
Nakashima, Ryoichi, and Takatsune Kumada. "Peripersonal versus extrapersonal visual scene information for egocentric direction and position perception." Quarterly Journal of Experimental Psychology 71, no. 5 (January 1, 2018): 1090–99. http://dx.doi.org/10.1080/17470218.2017.1310267.
Full textXu, Jie, Hanyuan Wang, Mingzhu Xu, Fan Yang, Yifei Zhou, and Xiaolong Yang. "Feature-Enhanced Occlusion Perception Object Detection for Smart Cities." Wireless Communications and Mobile Computing 2021 (March 29, 2021): 1–14. http://dx.doi.org/10.1155/2021/5544194.
Full textLee, Abigail, Robert Allison, and Laurie Wilcox. "Depth perception from successive occlusion." Journal of Vision 21, no. 9 (September 27, 2021): 1963. http://dx.doi.org/10.1167/jov.21.9.1963.
Full textPalmer, E. M., and P. J. Kellman. "(Mis)Perception of motion and form after occlusion: Anorthoscopic perception revisited." Journal of Vision 3, no. 9 (March 16, 2010): 251. http://dx.doi.org/10.1167/3.9.251.
Full textRamachandran, V. S., V. Inada, and G. Kiama. "Perception of illusory occlusion in apparent motion." Vision Research 26, no. 10 (January 1986): 1741–49. http://dx.doi.org/10.1016/0042-6989(86)90061-1.
Full textVallortigara, Giorgio, and Paola Bressan. "Occlusion and the perception of coherent motion." Vision Research 31, no. 11 (January 1991): 1967–78. http://dx.doi.org/10.1016/0042-6989(91)90191-7.
Full textHäkkinen, Jukka, and Göte Nyman. "Occlusion Constraints and Stereoscopic Slant." Perception 26, no. 1 (January 1997): 29–38. http://dx.doi.org/10.1068/p260029.
Full textOno, Hiroshi, Brian J. Rogers, Masao Ohmi, and Mika E. Ono. "Dynamic Occlusion and Motion Parallax in Depth Perception." Perception 17, no. 2 (April 1988): 255–66. http://dx.doi.org/10.1068/p170255.
Full textAndersen, George J., and James M. Cortese. "2-D contour perception resulting from kinetic occlusion." Perception & Psychophysics 46, no. 1 (January 1989): 49–55. http://dx.doi.org/10.3758/bf03208073.
Full textGillam, B. "Shape and meaning in the perception of occlusion." Journal of Vision 7, no. 9 (March 23, 2010): 608. http://dx.doi.org/10.1167/7.9.608.
Full textDissertations / Theses on the topic "Perception of Occlusion"
Daniels, Victoria. "Studies of occlusion and associated illusions." Thesis, University of Exeter, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241130.
Full textDuncan, Robert O. "Occlusion and the interpretation of visual motion : perceptual, oculomotor, and neuronal effects of context /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC IP addresses, 1999. http://wwwlib.umi.com/cr/ucsd/fullcit?p9956445.
Full textKelso, Carl Ryan. "Direct occlusion handling for high level image processing algorithms /." Online version of thesis, 2009. http://hdl.handle.net/1850/9497.
Full textMin, Rui. "Reconnaissance de visage robuste aux occultations." Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0020/document.
Full textFace recognition is an important technology in computer vision, which often acts as an essential component in biometrics systems, HCI systems, access control systems, multimedia indexing applications, etc. Partial occlusion, which significantly changes the appearance of part of a face, cannot only cause large performance deterioration of face recognition, but also can cause severe security issues. In this thesis, we focus on the occlusion problem in automatic face recognition in non-controlled environments. Toward this goal, we propose a framework that consists of applying explicit occlusion analysis and processing to improve face recognition under different occlusion conditions. We demonstrate in this thesis that the proposed framework is more efficient than the methods based on non-explicit occlusion treatments from the literature. We identify two new types of facial occlusions, namely the sparse occlusion and dynamic occlusion. Solutions are presented to handle the identified occlusion problems in more advanced surveillance context. Recently, the emerging Kinect sensor has been successfully applied in many computer vision fields. We introduce this new sensor in the context of face recognition, particularly in presence of occlusions, and demonstrate its efficiency compared with traditional 2D cameras. Finally, we propose two approaches based on 2D and 3D to improve the baseline face recognition techniques. Improving the baseline methods can also have the positive impact on the recognition results when partial occlusion occurs
Lindsey, David H. "Orthodontists' and Parents' Perspective of Occlusion in Varying Anterior-Posterior Positions: A Comparative Study." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/4758.
Full textBarnes, Timothy. "Visual depth perception from texture accretion and deletion: a neural model of figure-ground segregation and occlusion." Thesis, Boston University, 2012. https://hdl.handle.net/2144/31504.
Full textPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
Freezing is an effective defense strategy for some prey, because their predators rely on visual motion to distinguish objects from their surroundings. An object moving over a background progressively covers (deletes) and uncovers (accretes) background texture while simultaneously producing discontinuities in the optic flow field. These events unambiguously specify kinetic occlusion and can produce a crisp edge, depth perception, and figure-ground segregation between identically textured surfaces -- percepts which all disappear without motion. Given two abutting regions of uniform random texture with different motion velocities, one region will appear to be situated farther away and behind the other (i.e., the ground), if its texture is accreted or deleted at the boundary between the regions, irrespective of region and boundary velocities. Consequently, a region with moving texture appears farther away than a stationary region if the boundary is stationary, but it appears closer (i.e. the figure) if the boundary is moving coherently with the moving texture. The perception of kinetic occlusion requires the detection of an unexpected onset or offset of otherwise predictably moving or stationary contrast patches. A computational model of directional selectivity in visual cells is here extended to also detect motion onsets and offsets. The connectivity of these model cells not only affords the detection of local texture accretion and deletion events but also explains results showing that human reaction times differ for motion onsets versus offsets. These theorized cells are placed into a larger computational model of visual areas V1 and V2 to show how interactions between orientation- and direction-selective cells first create a motion-defined boundary and then signal texture accretion or deletion at that boundary. A weak speed-depth bias brings faster-moving texture regions forward in depth. This is consistent with percepts: the faster of two surfaces appears closer when moving parallel to the resulting emergent boundary between them (shearing motion). Activation of model occlusion detectors tuned to a particular velocity results in the model assigning the adjacent surface with a matching velocity to the far depth. These processes together reproduce human psychophysical reports of depth ordering for a representative set of all kinetic occlusion displays.
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Chambers, Destinee L. "Understanding Occlusion Inhibition: A Study of the Visual Processing of Superimposed Figures." Amherst, Mass. : University of Massachusetts Amherst, 2009. http://scholarworks.umass.edu/open_access_dissertations/6/.
Full textFiliz, Anil Yigit. "A New Approach For Better Load Balancing Of Visibility Detection And Target Acquisition Calculations." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612255/index.pdf.
Full textPatel, Nimisha Bhanuprasad. "Investigations into the neurophysiological basis of respiratory perception in humans using transient inspiratory occlusions." Thesis, Keele University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491697.
Full textDjezzar, Linda. "Contribution à l'étude acoustico-perceptive des occlusives du français." Nancy 1, 1995. http://www.theses.fr/1995NAN10009.
Full textBooks on the topic "Perception of Occlusion"
Oluikpe, George C. Visual guidance of locomotion: Occlusion of background by intervening object as information about the imminence of collision with the object. 1987.
Find full textAnderson, Barton L. A Layered Experience of Lightness and Color. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0037.
Full textBook chapters on the topic "Perception of Occlusion"
Song, Yang, Luis Goncalves, and Pietro Perona. "Monocular Perception of Biological Motion - Clutter and Partial Occlusion." In Lecture Notes in Computer Science, 719–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45053-x_46.
Full textHund, Marcus, and Bärbel Mertsching. "Occlusion as a Monocular Depth Cue Derived from Illusory Contour Perception." In KI 2009: Advances in Artificial Intelligence, 97–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04617-9_13.
Full textAmin, Akhter Al, Saad Hassan, and Matt Huenerfauth. "Effect of Occlusion on Deaf and Hard of Hearing Users’ Perception of Captioned Video Quality." In Lecture Notes in Computer Science, 202–20. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78095-1_16.
Full text"The Conditions for Perceiving Dynamic Occlusion of a Line." In Indirect Perception. The MIT Press, 1997. http://dx.doi.org/10.7551/mitpress/3727.003.0028.
Full textRogers, Brian. "5. Perception of a 3-D world." In Perception: A Very Short Introduction, 59–83. Oxford University Press, 2017. http://dx.doi.org/10.1093/actrade/9780198791003.003.0005.
Full textCraton, Lincoln G., and Albert Yonas. "Chapter 2 The Role of Motion in Infants' Perception of Occlusion." In The Development of attention - Research and Theory, 21–46. Elsevier, 1990. http://dx.doi.org/10.1016/s0166-4115(08)60449-5.
Full textFein, Elizabeth. "The Pathogen and the Package." In Living on the Spectrum, 133–65. NYU Press, 2020. http://dx.doi.org/10.18574/nyu/9781479864355.003.0006.
Full textVega, Julio, Eduardo Perdices, and José María Cañas. "Attentive Visual Memory for Robot Localization." In Robotic Vision, 406–36. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2672-0.ch021.
Full textConference papers on the topic "Perception of Occlusion"
Cuiral-Zueco, Ignacio, and Gonzalo Lopez-Nicolas. "Dynamic Occlusion Handling for Real Time Object Perception." In 2020 5th International Conference on Robotics and Automation Engineering (ICRAE). IEEE, 2020. http://dx.doi.org/10.1109/icrae50850.2020.9310850.
Full textLee, Szu-Han, Ya-Ting Chou, and Chih-Wei Tang. "Human perception inspired occlusion detection for stereo vision." In 2015 Picture Coding Symposium (PCS). IEEE, 2015. http://dx.doi.org/10.1109/pcs.2015.7170040.
Full textLesniak, Kevin, and Conrad S. Tucker. "Real-Time Occlusion Between Real and Digital Objects in Augmented Reality." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86346.
Full textFranz, Arthur, and Jochen Triesch. "Modeling the development of causality and occlusion perception in infants." In 2008 7th IEEE International Conference on Development and Learning (ICDL 2008). IEEE, 2008. http://dx.doi.org/10.1109/devlrn.2008.4640825.
Full textEidenberger, Robert, Raoul Zoellner, and Josef Scharinger. "Probabilistic occlusion estimation in cluttered environments for active perception planning." In 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2009. http://dx.doi.org/10.1109/aim.2009.5229779.
Full textZhang, Zixu, and Jaime Fisac. "Safe Occlusion-Aware Autonomous Driving via Game-Theoretic Active Perception." In Robotics: Science and Systems 2021. Robotics: Science and Systems Foundation, 2021. http://dx.doi.org/10.15607/rss.2021.xvii.066.
Full textIdesawa, Masanori, and Qi Zhang. "Occlusion cues and sustaining cues in 3D illusory object perception with binocular viewing." In AeroSense '97, edited by Steven K. Rogers. SPIE, 1997. http://dx.doi.org/10.1117/12.271541.
Full textFukiage, Taiki, Takeshi Oishi, and Katsushi Ikeuchi. "Reduction of contradictory partial occlusion in mixed reality by using characteristics of transparency perception." In 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2012. http://dx.doi.org/10.1109/ismar.2012.6402549.
Full textJain, Pranav, and Conrad Tucker. "Mobile Based Real-Time Occlusion Between Real and Digital Objects in Augmented Reality." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98440.
Full textFiorentino, Michele, Antonio E. Uva, and Giuseppe Monno. "Product Manufacturing Information Management in Interactive Augmented Technical Drawings." In ASME 2011 World Conference on Innovative Virtual Reality. ASMEDC, 2011. http://dx.doi.org/10.1115/winvr2011-5516.
Full textReports on the topic "Perception of Occlusion"
Finkel, Leif H. Visual Perception of Depth-from-Occlusion: A Neural Network Model. Fort Belvoir, VA: Defense Technical Information Center, July 1992. http://dx.doi.org/10.21236/ada253343.
Full textFinkel, Leif H. Visual Perception of Depth-from-Occlusion: A Neural Network Model. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada249771.
Full textFindel, Leif H. Visual Perception of Depth from Occlusion: A Neural Network Model. Fort Belvoir, VA: Defense Technical Information Center, January 1992. http://dx.doi.org/10.21236/ada249035.
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