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Stereo Matching of Planar Curves Composed of Time Stamped Points

Stereo Matching of Planar Curves Composed of Time Stamped Points
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摘要 Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points. Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points.
出处 《Journal of Southwest Jiaotong University(English Edition)》 2006年第4期315-322,共8页 西南交通大学学报(英文版)
基金 The National Natural Science Founda-tion of China (No.60135020) and the National Defence Key Pre-research Project of China (No.413010701-3)
关键词 Curve matching Epipolar geometry Time stamped points Binocular stereo vision Wide baseline Cross-ratio invariant Curve matching Epipolar geometry Time stamped points Binocular stereo vision Wide baseline Cross-ratio invariant
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参考文献12

  • 1Cordelia Schmid,Andrew Zisserman.The Geometry and Matching of Lines and Curves Over Multiple Views[J].International Journal of Computer Vision.2000(3)
  • 2Zhengyou Zhang,Gang Xu.A Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras[J].Journal of Mathematical Imaging and Vision.1998(3)
  • 3Hartley R I,Gupta R,Chang T.Stereo from uncalibrat-ed cameras[].Proceedings of Conference on Computer Vision and Pattern Recognition.1992
  • 4Kuan D T.Constraint and consistency in stereo matching[].ICASSP.1986
  • 5Lee S H,Leou J J.A dynamic programming approach to line segment matching in stereo vision[].Pattern Rec-ognition.1994
  • 6Yip R K K,Ho W P.A multi-level dynamic program-ming method for stereo line matching[].Pattern Recog-nition Letters.1998
  • 7Zhang Y N,,Gerbrands J J.Method for matching gener-al stereo planar curves[].Image and Vision Compu-ting.1995
  • 8Zhang W,,Zhang Q,Qu L,et al.A stereo matching algorithm based on multiresolution and epipolar con-straint[].ICIG.2004
  • 9Han J H,,Park J S.Contour matching using epipolar geometry[].IEEE Transactions on Analysis and Ma-chine Intelligence.2000
  • 10Hamanaka M,,Kenmochi Y,Sugimoto A.Discrete epi-polar geometry[].Discrete Geometry for Computer Imageryth International ConferenceDGCI.2005

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