Results 11 to 20 of about 19,336 (308)
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
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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
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An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion. [PDF]
Entropy (Basel), 2021 This paper proposes an improved stereo matching algorithm for vehicle speed measurement system based on spatial and temporal image fusion (STIF). Firstly, the matching point pairs in the license plate area with obviously abnormal distance to the camera ...
Yang L +5 more
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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
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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
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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
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Semiglobal Matching Results on the ISPRS Stereo Matching Benchmark [PDF]
, 2011 Digital surface models can be efficiently generated with automatic image matching from optical stereo images. The Working Group 4 of Commission I on "Geometric and Radiometric Modelling of Optical Spaceborne Sensors" provides a matching benchmark ...
Reinartz, Peter +3 more
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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
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2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Stereo is a prominent technique to infer dense depth maps from images, and deep learning further pushed forward the state-of-the-art, making end-to-end architectures unrivaled when enough data is available for training. However, deep networks suffer from significant drops in accuracy when dealing with new environments.
M. Poggi +3 more
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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
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