Cooperative stereo-motion: Matching and reconstruction

被引:9
|
作者
Dornaika, F [1 ]
Chung, R [1 ]
机构
[1] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Hong Kong, Peoples R China
关键词
correspondence problem; stereo-motion; perspective camera; 3D projective reconstruction; 3D Euclidean reconstruction; 3D-to-2D mapping;
D O I
10.1006/cviu.2000.0867
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the most interesting goals of computer vision is the 3D structure recovery of scenes. Traditionally, two cues are used: structure from motion and structure from stereo, two subfields with complementary sets of assumptions and techniques. This paper introduces a new general framework of cooperation between stereo and motion. This framework combines the advantages of both cues: (i) easy correspondence from motion and (ii) accurate 3D reconstruction from stereo. First, we show how the stereo matching can be recovered from motion correspondences using only geometric constraints. Second, we propose a method of 3D reconstruction of both binocular and monocular features using all stereo pairs in the case of a calibrated stereo rig. Third, we perform an analysis of the performance of the proposed framework as well as a comparison with an affine method. Experiments involving real and synthetic stereo pairs indicate that rich and reliable information can be derived from the proposed framework. They also indicate that robust 3D reconstruction can be obtained even with short image sequences. (C) 2000 Academic Press.
引用
收藏
页码:408 / 427
页数:20
相关论文
共 50 条
  • [21] A cooperative stereo matching algorithm for sewer inspection robots
    Ahrary, A
    Tian, L
    Kamata, S
    Ishikawa, M
    PROCEEDINGS OF THE SIXTH IASTED INTERNATIONAL CONFERENCE ON ROBOTICS AND APPLICATIONS, 2005, : 294 - 299
  • [22] Cooperative matching paradigm for the analysis of stereo image sequences
    Liao, WH
    Aggarwal, JK
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 1998, 9 (04) : 192 - 200
  • [23] Multi-Dimensional Cooperative Network for Stereo Matching
    Chen, Wei
    Jia, Xiaogang
    Wu, Mingfei
    Liang, Zhengfa
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (01): : 581 - 587
  • [24] Hilbert stereo reconstruction algorithm based on depth feature and stereo matching
    Kong, Weiyi
    Yang, Menglong
    Huang, Qinzhen
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 39 (05) : 8027 - 8038
  • [25] Cooperative Stereo-Zoom Matching for Disparity Computation
    Zhuo, Bo-Yang
    Lin, Huei-Yung
    VISAPP: PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS, VOL 4: VISAPP, 2020, : 157 - 164
  • [26] Performance analysis of cooperative Hopfield networks for stereo matching
    Zhou, Wenhui
    Xiang, Zhiyu
    Gu, Weikang
    COMPUTATIONAL INTELLIGENCE AND SECURITY, 2007, 4456 : 983 - 990
  • [27] Motion Assisted Video-based Stereo Matching
    Gao, Shengyu
    Wang, Hongyu
    Wang, Teng
    Wang, Yang
    Zhang, Xiangyu
    Lou, Xin
    2021 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (APCCAS 2021) & 2021 IEEE CONFERENCE ON POSTGRADUATE RESEARCH IN MICROELECTRONICS AND ELECTRONICS (PRIMEASIA 2021), 2021, : 57 - 60
  • [28] Motion Assisted Video-based Stereo Matching
    Gao, Shengyu
    Wang, Hongyu
    Wang, Teng
    Wang, Yang
    Zhang, Xiangyu
    Lou, Xin
    2021 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2021 and 2021 IEEE Conference on Postgraduate Research in Microelectronics and Electronics, PRIMEASIA 2021, 2021, : 57 - 60
  • [29] Stereo Matching for 3D Building Reconstruction
    Gupta, Gaurav
    Balasubramanian, R.
    Rawat, M. S.
    Bhargava, R.
    Krishna, B. Gopala
    ADVANCES IN COMPUTING, COMMUNICATION AND CONTROL, 2011, 125 : 522 - +
  • [30] Segment based stereo matching using cooperative Hopfield networks
    Zhou, Wenhui
    Xiang, Zhiyu
    Gu, Weikang
    2006 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PTS 1 AND 2, PROCEEDINGS, 2006, : 1845 - 1848