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....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.展开更多
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)
文摘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.
