Relevant bibliographies by topics / Binocular vision. Depth perception. Computer vision

Academic literature on the topic 'Binocular vision. Depth perception. Computer vision'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Binocular vision. Depth perception. Computer vision"

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Fazlyyyakhmatov, Marsel, Nataly Zwezdochkina, and Vladimir Antipov. "The EEG Activity during Binocular Depth Perception of 2D Images." Computational Intelligence and Neuroscience 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/5623165.

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The central brain functions underlying a stereoscopic vision were a subject of numerous studies investigating the cortical activity during binocular perception of depth. However, the stereo vision is less explored as a function promoting the cognitive processes of the brain. In this work, we investigated a cortical activity during the cognitive task consisting of binocular viewing of a false image which is observed when the eyes are refocused out of the random-dot stereogram plane (3D phenomenon). The power of cortical activity before and after the onset of the false image perception was assessed using the scull EEG recording. We found that during stereo perception of the false image the power of alpha-band activity decreased in the left parietal area and bilaterally in frontal areas of the cortex, while activity in beta-1, beta-2, and delta frequency bands remained to be unchanged. We assume that this suppression of alpha rhythm is presumably associated with increased attention necessary for refocusing the eyes at the plane of the false image.
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Idesawa, Masanori. "3-D Illusory Phenomena with Binocular Viewing and Computer Vision." Journal of Robotics and Mechatronics 4, no. 3 (June 20, 1992): 249–55. http://dx.doi.org/10.20965/jrm.1992.p0249.

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The human visual system can perceive 3-D information of an object by using disparity between two eyes, gradient of illumination (shading), occlusion, textures and their perspective and so on. Consequently, the disparity and the occlusion observed with binocular viewing seems to be the most important cues to get 3-D information. For the artificial realization of the visual function such as in computer vision or robot vision system, it seems to be a clever way to learn from the human visual mechanism. Recently, the author found a new type of illusion. When the visual stimuli of disparity are given only partially along the contour of an object, human visual system can perceive the 3-D surface (not only plane but also curved) of the object where there are no physical visual stimuli to get depth information. The interactions between the perceived illusory surface (occlusion, intersection and transparency) can be recognized. These newly found illusory phenomena have close relations with the visual function of 3-D space perception and can provide a new paradigm in the field of computer vision and human interface.
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Sakai, Ko, Mitsuharu Ogiya, and Yuzo Hirai. "Decoding of depth and motion in ambiguous binocular perception." Journal of the Optical Society of America A 28, no. 7 (June 20, 2011): 1445. http://dx.doi.org/10.1364/josaa.28.001445.

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Yang, Fan, and Yutai Rao. "Vision-Based Intelligent Vehicle Road Recognition and Obstacle Detection Method." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 07 (October 18, 2019): 2050020. http://dx.doi.org/10.1142/s0218001420500202.

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With the development of the world economy and the accelerating process of urbanization, cars have brought great convenience to people’s lives and activities, and have become an indispensable means of transportation. Intelligent vehicles have the important significance of reducing traffic accidents, improving transportation capacity and broad market prospects, and can lead the future development of the automotive industry, so they have received extensive attention. In the existing intelligent vehicle system, the laser radar is a well-deserved protagonist because of its excellent speed and precision. It is an indispensable part of achieving high-precision positioning, but to some extent, the price hindering its marketization is a major factor. Compared with lidar sensors, vision sensors have the advantages of fast sampling rate, light weight, low energy consumption and low price. Therefore, many domestic and foreign research institutions have listed them as the focus of research. However, the current vision-based intelligent vehicle environment sensing technology is also susceptible to factors such as illumination, climate and road type, resulting in insufficient accuracy and real-time performance of the algorithm. This paper takes the environment perception of intelligent vehicles as the research object, and conducts in-depth research on the existing problems in road recognition and obstacle detection algorithms, including road image vanishing point detection, road image segmentation problem, road scene based on binocular vision. Three-dimensional reconstruction and obstacle detection technology.
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Surdick, R. Troy, Elizabeth T. Davis, Robert A. King, and Larry F. Hodges. "The Perception of Distance in Simulated Visual Displays:A Comparison of the Effectiveness and Accuracy of Multiple Depth Cues Across Viewing Distances." Presence: Teleoperators and Virtual Environments 6, no. 5 (October 1997): 513–31. http://dx.doi.org/10.1162/pres.1997.6.5.513.

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The ability effectively and accurately to simulate distance in virtual and augmented reality systems is a challenge currently facing R&D. To examine this issue, we separately tested each of seven visual depth cues (relative brightness, relative size, relative height, linear perspective, foreshortening, texture gradient, and stereopsis) as well as the condition in which all seven of these cues were present and simultaneously providing distance information in a simulated display. The viewing distances were 1 and 2 m. In developing simulated displays to convey distance and depth there are three questions that arise. First, which cues provide effective depth information (so that only a small change in the depth cue results in a perceived change in depth)? Second, which cues provide accurate depth information (so that the perceived distance of two equidistant objects perceptually matches)? Finally, how does the effectiveness and accuracy of these depth cues change as a function of the viewing distance? Ten college-aged subjects were tested with each depth-cue condition at both viewing distances. They were tested using a method of constant stimuli procedure and a modified Wheat-stone stereoscopic display. The perspective cues (linear perspective, foreshortening, and texture gradient) were found to be more effective than other depth cues, while effectiveness of relative brightness was vastly inferior. Moreover, relative brightness, relative height, and relative size all significantly decreased in effectiveness with an increase in viewing distance. The depth cues did not differ in terms of accuracy at either viewing distance. Finally, some subjects experienced difficulty in rapidly perceiving distance information provided by stereopsis, but no subjects had difficulty in effectively and accurately perceiving distance with the perspective information used in our experiment. A second experiment demonstrated that a previously stereo-anomalous subject could be trained to perceive stereoscopic depth in a binocular display. We conclude that the use of perspective cues in simulated displays may be more important than the other depth cues tested because these cues are the most effective and accurate cues at both viewing distances, can be easily perceived by all subjects, and can be readily incorporated into simpler, less complex displays (e.g., biocular HMDs) or more complex ones (e.g., binocular or see-through HMDs).
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Ishimura, G. "Hand Action in a Radial Direction Captures Visual Motion in Depth." Perception 25, no. 1_suppl (August 1996): 138. http://dx.doi.org/10.1068/v96p0116.

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Transversal hand action in the frontoparallel plane biases the perception of bistable visual motion. This has been called action capture. In daily behaviour, however, hand action in a ‘radial’ direction from the head might be more important, because we frequently reach our hand for an object in front of us while guiding the action with vision. The purpose of this study was to measure the strength of action capture in the radial direction. Horizontal luminance gratings were placed above and below the fixation point. Binocular disparity, perspective contour, and spatial frequency gradient cues were attached to the gratings so that they simulated the ‘ceiling’ and the ‘floor’ of a long corridor. The display was reflected on a tilted mirror to face upward. The subject looked into the display and moved his/her dominant hand toward, or away from, the face behind the mirror. Just after the action onset, detected by the computer, one of the two gratings (the ceiling or the floor) flickered in short period to simulate bistable visual motion in depth (approaching or departing). The subject indicated the perceived motion direction in the frontoparallel plane using a 2AFC (upward or downward) method. The results showed that perceived motion was significantly biased to the ‘departing’ direction when the hand moved ‘away from’ the face, and it was biased to the ‘approaching’ direction when the hand moved ‘toward’ it. It is concluded that action capture occurs not only in transversal but also in radial movements.
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Naceri, Abdeldjallil, Ryad Chellali, and Thierry Hoinville. "Depth Perception Within Peripersonal Space Using Head-Mounted Display." Presence: Teleoperators and Virtual Environments 20, no. 3 (June 1, 2011): 254–72. http://dx.doi.org/10.1162/pres_a_00048.

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In this paper, we address depth perception in the peripersonal space within three virtual environments: poor environment (dark room), reduced cues environment (wireframe room), and rich cues environment (a lit textured room). Observers binocularly viewed virtual scenes through a head-mounted display and evaluated the egocentric distance to spheres using visually open-loop pointing tasks. We conducted two different experiments within all three virtual environments. The apparent size of the sphere was held constant in the first experiment and covaried with distance in the second one. The results of the first experiment revealed that observers more accurately estimated depth in the rich virtual environment compared to the visually poor and the wireframe environments. Specifically, observers' pointing errors were small in distances up to 55 cm, and increased with distance once the sphere was further than 55 cm. Individual differences were found in the second experiment. Our results suggest that the quality of virtual environments has an impact on distance estimation within reaching space. Also, manipulating the targets' size cue led to individual differences in depth judgments. Finally, our findings confirm the use of vergence as an absolute distance cue in virtual environments within the arm's reaching space.
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Moro, Stefania S., and Jennifer K. E. Steeves. "Intact Dynamic Visual Capture in People With One Eye." Multisensory Research 31, no. 7 (2018): 675–88. http://dx.doi.org/10.1163/22134808-20181311.

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Abstract Observing motion in one modality can influence the perceived direction of motion in a second modality (dynamic capture). For example observing a square moving in depth can influence the perception of a sound to increase in loudness. The current study investigates whether people who have lost one eye are susceptible to audiovisual dynamic capture in the depth plane similar to binocular and eye-patched viewing control participants. Partial deprivation of the visual system from the loss of one eye early in life results in changes in the remaining intact senses such as hearing. Linearly expanding or contracting discs were paired with increasing or decreasing tones and participants were asked to indicate the direction of the auditory stimulus. Magnitude of dynamic visual capture was measured in people with one eye compared to eye-patched and binocular viewing controls. People with one eye have the same susceptibility to dynamic visual capture as controls, where they perceived the direction of the auditory signal to be moving in the direction of the incongruent visual signal, despite previously showing a lack of visual dominance for audiovisual cues. This behaviour may be the result of directing attention to the visual modality, their partially deficient sense, in order to gain important information about approaching and receding stimuli which in the former case could be life-threatening. These results contribute to the growing body of research showing that people with one eye display unique accommodations with respect to audiovisual processing that are likely adaptive in each unique sensory situation.
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Bridge, Holly. "Effects of cortical damage on binocular depth perception." Philosophical Transactions of the Royal Society B: Biological Sciences 371, no. 1697 (June 19, 2016): 20150254. http://dx.doi.org/10.1098/rstb.2015.0254.

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Stereoscopic depth perception requires considerable neural computation, including the initial correspondence of the two retinal images, comparison across the local regions of the visual field and integration with other cues to depth. The most common cause for loss of stereoscopic vision is amblyopia, in which one eye has failed to form an adequate input to the visual cortex, usually due to strabismus (deviating eye) or anisometropia. However, the significant cortical processing required to produce the percept of depth means that, even when the retinal input is intact from both eyes, brain damage or dysfunction can interfere with stereoscopic vision. In this review, I examine the evidence for impairment of binocular vision and depth perception that can result from insults to the brain, including both discrete damage, temporal lobectomy and more systemic diseases such as posterior cortical atrophy. This article is part of the themed issue ‘Vision in our three-dimensional world’.
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YASUOKA, Akiko, and Masaaki OKURA. "Binocular depth perception of objects with peripheral vision (5):." Proceedings of the Annual Convention of the Japanese Psychological Association 74 (September 20, 2010): 2AM113. http://dx.doi.org/10.4992/pacjpa.74.0_2am113.

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Dissertations / Theses on the topic "Binocular vision. Depth perception. Computer vision"

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Tsang, Kong Chau. "Preference for phase-based disparity in a neuromorphic implementation of the binocular energy model /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202003%20TSANG.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.
Includes bibliographical references (leaves 64-66). Also available in electronic version. Access restricted to campus users.
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Val, Petran. "BINOCULAR DEPTH PERCEPTION, PROBABILITY, FUZZY LOGIC, AND CONTINUOUS QUANTIFICATION OF UNIQUENESS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1504749439893027.

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Gampher, John Eric. "Perception of motion-in-depth induced motion effects on monocular and binocular cues /." Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2009r/gampher.pdf.

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Thesis (Ph. D.)--University of Alabama at Birmingham, 2008.
Title from PDF title page (viewed Mar. 30, 2010). Additional advisors: Franklin R. Amthor, James E. Cox, Timothy J. Gawne, Rosalyn E. Weller. Includes bibliographical references (p. 104-114).
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Chan, Y. M. "Depth perception in visual images." Thesis, University of Brighton, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380238.

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Zotov, Alexander. "Models of disparity gradient estimation in the visual cortex." Birmingham, Ala. : University of Alabama at Birmingham, 2007. https://www.mhsl.uab.edu/dt/2008r/zotov.pdf.

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Parton, Andrew D. "The role of binocular disparity and motion parallax information in the perception of depth and shape of physical and simulated stimuli." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/843854/.

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A series of experiments is reported that examined the perception of the depth structure of a visual scene on the basis of binocular disparity and motion parallax information. Initial experiments (2.1-2.4) revealed that there are considerable differences in the perception of depth in computer simulated surfaces specified by each cue individually. These differences were interpreted as indicating a variation in the relative sensitivity of the visual system to different components of the geometric transformations generated between retinal images within the two domains. Subsequent experiments assessed observers' perception of depth, on the basis of disparity and/or parallax information, in configurations of point light sources in a dark limited cue environment viewed (i) directly (experiments 3.1, 3.2, 3.3 and 5) and (ii) through a head mounted CRT display (experiments 4.1-4.3). They showed that in these viewing conditions the visual system cannot derive a metric (Euclidean) representation of scene structure but it has access to a range of strategies (and consequently representations) that may enable it to complete tasks accurately. The strategy used depended upon the range of available information sources, an assessment of their reliability and the nature of the experimental task. Two final experiments examined the effect of increasing the available depth cues by (i) performing a task in an illuminated structured viewing environment and (ii) introducing surface texture cues. They showed that biases in depth perception persist in such environments and that they cannot be entirely explained by conflicting depth information signalled by accommodation (Frisby et al, 1996). It is argued that strong fusion models of depth cue interaction best describe the range of interactions found across of the all experiments. However, there are limitations on the types of strong interaction used by the visual system, i.e. no evidence was found for Richards' (1985) proposal that the simultaneous presence of disparity and motion information allow the recovery depth structure.
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Grafton, Catherine E. "Binocular vision and three-dimensional motion perception : the use of changing disparity and inter-ocular velocity differences." Thesis, University of St Andrews, 2011. http://hdl.handle.net/10023/1922.

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This thesis investigates the use of binocular information for motion-in-depth (MID) perception. There are at least two different types of binocular information available to the visual system from which to derive a perception of MID: changing disparity (CD) and inter-ocular velocity differences (IOVD). In the following experiments, we manipulate the availability of CD and IOVD information in order to assess the relative influence of each on MID judgements. In the first experiment, we assessed the relative effectiveness of CD and IOVD information for MID detection, and whether the two types of binocular information are processed by separate mechanisms with differing characteristics. Our results suggest that, both CD and IOVD information can be utilised for MID detection, yet, the relative dependence on either of these types of MID information varies between observers. We then went on to explore the contribution of CD and IOVD information to time-to-contact (TTC) perception, whereby an observer judges the time at which an approaching stimulus will contact them. We confirmed that the addition of congruent binocular information to looming stimuli can influence TTC judgements, but that there is no influence from binocular information indicating no motion. Further to this, we found that observers could utilise both CD and IOVD for TTC judgements, although once again, individual receptiveness to CD and/or IOVD information varied. Thus, we demonstrate that the human visual system is able to process both CD and IOVD information, but the influence of either (or both) of these cues on an individual’s perception has been shown to be mutually independent.
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Riddell, Patricia Mary. "Vergence eye movements and dyslexia." Thesis, University of Oxford, 1987. http://ora.ox.ac.uk/objects/uuid:fc695d53-073a-467d-bc8d-8d47c0b9321e.

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Ulusoy, Ilkay. "Active Stereo Vision: Depth Perception For Navigation, Environmental Map Formation And Object Recognition." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/12604737/index.pdf.

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In very few mobile robotic applications stereo vision based navigation and mapping is used because dealing with stereo images is very hard and very time consuming. Despite all the problems, stereo vision still becomes one of the most important resources of knowing the world for a mobile robot because imaging provides much more information than most other sensors. Real robotic applications are very complicated because besides the problems of finding how the robot should behave to complete the task at hand, the problems faced while controlling the robot&rsquo
s internal parameters bring high computational load. Thus, finding the strategy to be followed in a simulated world and then applying this on real robot for real applications is preferable. In this study, we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with active stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot. By applying our disparity algorithm, depth map for the current stereo view is extracted. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, the robot turns around it, obtains stereo images from different directions and extracts the model of the object in 3D. Using the available set of possible objects, it recognizes the object.
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McIntire, John Paul. "Investigating the Relationship between Binocular Disparity, Viewer Discomfort, and Depth Task Performance on Stereoscopic 3D Displays." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1400790668.

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Books on the topic "Binocular vision. Depth perception. Computer vision"

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McCoun, Jacques. Binocular vision: Development, depth perception, and disorders. Hauppauge, N.Y: Nova Science Publishers, 2009.

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Vision in 3D environments. Cambridge: Cambridge University Press, 2011.

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1946-, Vaina Lucia, ed. From the retina to the neocortex: Selected papers of David Marr. Boston: Birkhäuser, 1991.

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J, Rogers Brian, ed. Binocular vision and stereopsis. New York: Oxford University Press, 1995.

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Statham, Alison Kathryn. Human binocular vision and stereopsis: Combining first and second order cues in stereo depth perception. Birmingham: University of Birmingham, 1998.

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From images to surfaces: A computational study of the human early visual system. Cambridge, Mass: MIT Press, 1986.

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Jacques, McCoun, and Reeves Lucien, eds. Binocular vision: Development, depth perception, and disorders. Hauppauge, N.Y: Nova Science Publishers, 2009.

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Book chapters on the topic "Binocular vision. Depth perception. Computer vision"

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Stidwill, David, and Robert Fletcher. "Depth Perception." In Normal Binocular Vision, 172–95. West Sussex, UK: John Wiley & Sons, Ltd., 2014. http://dx.doi.org/10.1002/9781118788684.ch11.

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Patterson, Robert Earl. "Binocular Vision and Depth Perception." In Handbook of Visual Display Technology, 1–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-35947-7_9-2.

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Patterson, Robert Earl. "Binocular Vision and Depth Perception." In Handbook of Visual Display Technology, 121–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-79567-4_9.

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Patterson, Robert Earl. "Binocular Vision and Depth Perception." In Handbook of Visual Display Technology, 143–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-14346-0_9.

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Guo, Xinqing, Zhang Chen, Siyuan Li, Yang Yang, and Jingyi Yu. "Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs." In Pattern Recognition and Computer Vision, 353–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31726-3_30.

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Polláková, Jana, Miroslav Laco, and Wanda Benesova. "Depth Perception Tendencies in the 3-D Environment of Virtual Reality." In Computer Vision and Graphics, 142–50. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59006-2_13.

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Orghidan, Radu, El Mustapha Mouaddib, and Joaquim Salvi. "A Computer Vision Sensor for Panoramic Depth Perception." In Pattern Recognition and Image Analysis, 153–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492429_19.

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Jin, Yongsik, Mallipeddi Rammohan, Giyoung Lee, and Minho Lee. "Autonomous Depth Perception of Humanoid Robot Using Binocular Vision System Through Sensorimotor Interaction with Environment." In Neural Information Processing, 554–61. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26535-3_63.

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"Binocular vision and depth perception." In An Introduction to the Biology of Vision, 164–82. Cambridge University Press, 1996. http://dx.doi.org/10.1017/cbo9781139174473.011.

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Howard, Ian P., and Brian J. Rogers. "Binocular disparity and depth perception." In Perceiving in DepthVolume 2 Stereoscopic Vision, 385–432. Oxford University Press, 2012. http://dx.doi.org/10.1093/acprof:oso/9780199764150.003.0350.

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Conference papers on the topic "Binocular vision. Depth perception. Computer vision"

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Su, Zhi-bin, Dong-rui Li, Hui Ren, and Ling-feng Chen. "Evaluation of depth perception based on binocular stereo vision." In 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2017. http://dx.doi.org/10.1109/fskd.2017.8393240.

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Hong Liu, Jiexin Pu, and Qinghua Zhang. "Binocular stereo vision based indoor scene perception." In 2011 3rd International Conference on Computer Research and Development (ICCRD). IEEE, 2011. http://dx.doi.org/10.1109/iccrd.2011.5764078.

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Lackner, Kristof, Atanas Boev, and Atanas Gotchev. "Binocular depth perception: Does head parallax help people see better in depth?" In 2014 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON 2014). IEEE, 2014. http://dx.doi.org/10.1109/3dtv.2014.6874746.

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Hel-Or, Hagit, Yacov Hel-Or, and Renato Keshet. "Depth-Stretch: Enhancing Depth Perception Without Depth." In 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017. http://dx.doi.org/10.1109/cvprw.2017.137.

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Weihua, Xie, and Feng Shuang. "Baseline Length Estimation Method Based on Binocular Stereo Vision Perception." In 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE). IEEE, 2019. http://dx.doi.org/10.1109/eitce47263.2019.9095147.

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Iizuka, Masayuki, Masato Nishimoto, Hiroyasu Shirafuji, Yoshio Ookuma, Yoshio Nakashima, and Mamoru Takamatsu. "Psychophysical effect of retouched and modified digital stereograms for binocular vision on depth perception." In Electronic Imaging 2004, edited by Tung H. Jeong and Hans I. Bjelkhagen. SPIE, 2004. http://dx.doi.org/10.1117/12.523918.

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Lu, Yang, and Wamg Rong-ben. "Research on Environmental Perception Technology for Menology Environments Based on Binocular Vision." In 2009 WRI World Congress on Computer Science and Information Engineering. IEEE, 2009. http://dx.doi.org/10.1109/csie.2009.301.

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Chuan-xu, Wang, and Sun Ying-he. "A New Method of Depth Measurement with Binocular Vision Based on SURF." In 2009 Second International Workshop on Computer Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.733.

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"COMPUTATIONAL MODEL OF DEPTH PERCEPTION BASED ON FIXATIONAL EYE MOVEMENTS." In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002829203280333.

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"DEPTH PERCEPTION MODEL EXPLOITING BLURRING CAUSED BY RANDOM SMALL CAMERA MOTIONS." In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003817403290334.

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