Results 51 to 60 of about 1,867,265 (234)
FADNet: A Fast and Accurate Network for Disparity Estimation [PDF]
IEEE International Conference on Robotics and Automation, 2020 Deep neural networks (DNNs) have achieved great success in the area of computer vision. The disparity estimation problem tends to be addressed by DNNs which achieve much better prediction accuracy in stereo matching than traditional hand-crafted feature ...
Qiang Wang +4 more
semanticscholar +1 more source
, 2011 When performing image operations involving Structuring Element (SE) and many transforms it is required that the outside of the image be padded with zeros or ones depending on the operation.
J. Grindley, A. Tickle, Lin Jiang
semanticscholar +1 more source
A Survey of Learning Approaches and Application for 3D Vision
MATEC Web of Conferences, 2018 Three-dimensional (3D) vision extracted from the stereo images or reconstructed from the two-dimensional (2D) images is the most effective topic in computer vision and video surveillance.
Lu Luanhao
doaj +1 more source
IEEE International Conference on Multimedia and Expo, 2021 Indoor robotics applications heavily rely on scene understanding and reconstruction. Compared to monocular vision, stereo vision methods are more promising to produce accurate geometrical information, such as surface normal and depth/disparity.
Qiang Wang +5 more
semanticscholar +1 more source
Abnormal depth perception from motion parallax in amblyopic observers [PDF]
, 1999 Many similarities exist between the perception of depth from binocular stereopsis and that from motion parallax. Moreover, Rogers (1984, cited in, Howard, I. P., & Rogers, B. J. (1995). Binocular vision and stereopsis.
Nawrot, Mark, Thompson, Angela M
core +1 more source
Bayesian Learning for Disparity Map Refinement for Semi-Dense Active Stereo Vision [PDF]
arXiv, 2022 A major focus of recent developments in stereo vision has been on how to obtain accurate dense disparity maps in passive stereo vision. Active vision systems enable more accurate estimations of dense disparity compared to passive stereo. However, subpixel-accurate disparity estimation remains an open problem that has received little attention.
arxiv
Disparity Refinement Process Based On Ransac Plane Fitting For Machine Vision Applications
, 2018 This paper presents a new disparity map refinement process for stereo matching algorithm and the refinement stage that will be implemented by partitioning the place or mask image and re-projected to the preliminary disparity images.
R. A. Hamzah +4 more
semanticscholar +1 more source
Enhancing Fairness in Face Detection in Computer Vision Systems by Demographic Bias Mitigation
AAAI/ACM Conference on AI, Ethics, and Society, 2022 Fairness has become an important agenda in computer vision and artificial intelligence. Recent studies have shown that many computer vision models and datasets exhibit demographic biases and proposed mitigation strategies.
Yu Yang +8 more
semanticscholar +1 more source
Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals [PDF]
, 2016 Reconstruction of the tridimensional geometry of a visual scene using the binocular disparity information is an important issue in computer vision and mobile robotics, which can be formulated as a Bayesian inference problem.
Bessière, Pierre +2 more
core +3 more sources
arXiv, 2021 Most of stereo vision works are focusing on computing the dense pixel disparity of a given pair of left and right images. A camera pair usually required lens undistortion and stereo calibration to provide an undistorted epipolar line calibrated image pair for accurate dense pixel disparity computation. Due to noise, object occlusion, repetitive or lack
arxiv