Results 11 to 20 of about 19,312 (309)
Research and Development of Binocular Stereo Matching Algorithm
Jisuanji kexue yu tansuo, 2020 Binocular stereo vision has the advantages of low cost and wide applicability. It is extensively used in object recognition, object detection and has become the research focuses in the field of computer vision.
ZHAO Chenyuan, LI Wenxin, ZHANG Qingxi
doaj +1 more source
Self-Supervised Stereo Matching Method Based on SRWP and PCAM for Urban Satellite Images
Remote Sensing, 2022 In this paper, we propose a self-supervised stereo matching method based on superpixel random walk pre-matching (SRWP) and parallax-channel attention mechanism (PCAM). Our method is divided into two stages, training and testing.
Wen Chen, Hao Chen, Shuting Yang
doaj +1 more source
Stereo Object Matching Network [PDF]
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information. Unlike existing stereo matching methods that exclusively focus on the pixel-level correspondence between stereo images within a volumetric space (i.e., cost volume), we exploit this volumetric structure in
Jaesung Choe +3 more
openaire +2 more sources
Dense spatio‐temporal stereo matching for intelligent driving systems
IET Image Processing, 2021 This paper addresses the problem of matching stereo images acquired by a stereo system mounted aboard an intelligent vehicle. The main idea behind the new method consists in involving temporal matching between a current stereo pair and its preceding one ...
Zakaria Kerkaou +3 more
doaj +1 more source
IEEE Access, 2023 While stereo matching methods have great progress in recent years, they still face several formidable challenges. These challenges mainly include how to fully utilize global context and depth semantic information for depth feature extraction while ...
Bowen Jiao +4 more
doaj +1 more source
IET Computer Vision, 2022 Stereo matching is an important computer vision tool for three‐dimensional (3D) positioning, 3D visual representation, precision detection and recognition with 3D information.
Chih‐Hsuan Huang, Jar‐Ferr Yang
doaj +1 more source
EXPERIMENT ON PRODUCING DISPARITY MAPS FROM AERIAL STEREO IMAGES USING UNSUPERVISED AND SUPERVISED METHODS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Recent advancement in hardware and software provides the possibility of realizing full automation in stereo-image tasks. This paper investigated disparity map generation from aerial images with different methods: unsupervised method and supervised ...
L. Zhu +3 more
doaj +1 more source
Computer Vision and Image Understanding, 2005 A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given the observed stereo images. A mixed sampling and deterministic strategy is adopted to balance between effectiveness and efficiency: the parameters are estimated via Markov ...
Li Cheng 0001, Terry Caelli
openaire +2 more sources
Local Stereo Matching Based on Support Weight With Motion Flow for Dynamic Scene
IEEE Access, 2016 Stereo matching is one of the most important and challenging subjects in the field of stereo vision. The disparity obtained in stereo matching can represent depth information in 3-D world to a great extent and shows great importance in stereo field.
Jiachen Yang +5 more
doaj +1 more source
HIGH-PRECISION DEM PRODUCTION FOR SPACEBORNE STEREO SAR IMAGES BASED ON SIFT MATCHING AND REGION-BASED LEAST SQUARES MATCHING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Generally, there are two ways to generate Digital Elevation Model (DEM) using synthetic aperture radar (SAR) data, which are Interferometer Synthetic Aperture Radar(InSAR) and radargrammetry. Considering the disadvantages of InSAR data, such as the limit
S. Xiaotian, Z. Guo, Z. Guo, W. Xia
doaj +1 more source