A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images [PDF]
arXiv, 2023 Purpose: Stereo matching methods that enable depth estimation are crucial for visualization enhancement applications in computer-assisted surgery (CAS). Learning-based stereo matching methods are promising to predict accurate results on laparoscopic images. However, they require a large amount of training data, and their performance may be degraded due
arxiv
A New Structure of Stereo Algorithm Using Pixel Based Differences and Weighted Median Filter [PDF]
, 2019 This paper proposed a new algorithm for stereo vision system to obtain depth map or disparity map. The proposed stereo vision algorithm consists of three stages, matching cost computation, disparity optimization and disparity refinement.
Gan, Y., Hamzah, R.A., Nik Anwar, N.S.
core +1 more source
Stixel Based Scene Understanding for Autonomous Vehicles [PDF]
, 2017 We propose a stereo vision based obstacle detection and scene segmentation algorithm appropriate for autonomous vehicles. Our algorithm is based on an innovative extension of the Stixel world, which neglects computing a disparity map.
Aouf, N. +3 more
core +2 more sources
Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors [PDF]
2019 European Conference on Mobile Robots (ECMR), 2019 Event-based cameras are biologically inspired sensors that output asynchronous pixel-wise brightness changes in the scene called events. They have a high dynamic range and temporal resolution of a microsecond, opposed to standard cameras that output frames at fixed frame rates and suffer from motion blur.
Ivan Marković +2 more
openaire +4 more sources
Two independent mechanisms for motion-in-depth perception : evidence from individual differences [PDF]
, 2010 Our forward-facing eyes allow us the advantage of binocular visual information: using the tiny differences between right and left eye views to learn about depth and location in three dimensions.
Harris, Julie +2 more
core +1 more source
BidNet: Binocular Image Dehazing Without Explicit Disparity Estimation
Computer Vision and Pattern Recognition, 2020 Heavy haze results in severe image degradation and thus hampers the performance of visual perception, object detection, etc. On the assumption that dehazed binocular images are superior to the hazy ones for stereo vision tasks such as 3D object detection
Yanwei Pang +4 more
semanticscholar +1 more source
A Novel Disparity Transformation Algorithm for Road Segmentation [PDF]
arXiv, 2018 The disparity information provided by stereo cameras has enabled advanced driver assistance systems to estimate road area more accurately and effectively. In this paper, a novel disparity transformation algorithm is proposed to extract road areas from dense disparity maps by making the disparity value of the road pixels become similar.
arxiv
Stereo Disparity through Cost Aggregation with Guided Filter
Image Processing On Line, 2014 Estimating the depth, or equivalently the disparity, of a stereo scene is a challenging problem in computer vision. The method proposed by Rhemann et al.
Pauline Tan, Pascal Monasse
doaj +1 more source
Motion Parallax is Asymptotic to Binocular Disparity [PDF]
arXiv, 2010 Researchers especially beginning with (Rogers & Graham, 1982) have noticed important psychophysical and experimental similarities between the neurologically different motion parallax and stereopsis cues. Their quantitative analysis relied primarily on the "disparity equivalence" approximation.
arxiv
Stereo Vision for 3D Measurement in Robot Systems
Journal of Engineering and Sustainable Development, 2013 The major obstacle in the application of stereo vision to extract 3D information is the error in disparity map and highly computational cost at conventional computers.
Muhyi AL-Azawi +2 more
doaj