3D Surface Reconstruction Using A Two-Step Stereo Matching Method Assisted with Five Projected Patterns
Refereed conference paper presented and published in conference proceedings

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摘要Three-dimensional vision plays an important role in robotics. In this paper, we present a 3D surface reconstruction scheme based on combination of stereo matching and pattern projection. A two-step matching scheme is proposed to establish reliable correspondence between stereo images with high computation efficiency and accuracy. The first step (coarse matching) can quickly find the correlation candidates, and the second step (precise matching) is responsible for determining the most precise correspondence within the candidates. Two phase maps serve as codewords and are utilized in the two-step stereo matching, respectively. The phase maps are derived from phase-shifting patterns to provide robustness to the background noises. Only five patterns are required, which reduces the image acquisition time. Moreover, the precision is further enhanced by applying a correspondence refinement algorithm. The precision and accuracy are validated by experiments on standard objects. Furthermore, various experiments are conducted to verify the capability of the proposed method, which includes the complex object reconstruction, the high-resolution reconstruction, and the occlusion avoidance. The real-time experimental results are also provided.
著者Congying Sui, Kejing He, Congyi Lyu, Zerui Wang, Yun-Hui Liu
會議名稱2019 International Conference on Robotics and Automation (ICRA)
會議開始日20.05.2019
會議完結日24.05.2019
會議地點Montreal
會議國家/地區加拿大
會議論文集題名2019 International Conference on Robotics and Automation (ICRA)
詳細描述Three-dimensional vision plays an important role in robotics. In this paper, we present a 3D surface reconstruction scheme based on combination of stereo matching and pattern projection. A two-step matching scheme is proposed to establish reliable correspondence between stereo images with high computation efficiency and accuracy. The first step (coarse matching) can quickly find the correlation candidates, and the second step (precise matching) is responsible for determining the most precise correspondence within the candidates. Two phase maps serve as codewords and are utilized in the two-step stereo matching, respectively. The phase maps are derived from phase-shifting patterns to provide robustness to the background noises. Only five patterns are required, which reduces the image acquisition time. Moreover, the precision is further enhanced by applying a correspondence refinement algorithm. The precision and accuracy are validated by experiments on standard objects. Furthermore, various experiments are conducted to verify the capability of the proposed method, which includes the complex object reconstruction, the high-resolution reconstruction, and the occlusion avoidance. The real-time experimental results are also provided.
出版年份2019
出版社IEEE
頁次6080 - 6086
國際標準書號978-1-5386-6026-3
語言英式英語
關鍵詞correlation methods, image matching, image reconstruction, image resolution, robot vision, solid modelling, stereo image processing, surface reconstruction, three-dimensional vision, 3D surface reconstruction scheme, stereo matching pattern projection, stereo images, phase maps, phase-shifting patterns, image acquisition time, correspondence refinement algorithm, high-resolution reconstruction, object reconstruction, two-step stereo matching method, Three-dimensional displays, Image reconstruction, Surface reconstruction, Cameras, Robots, Pattern matching, Robustness

上次更新時間 2020-25-11 於 23:59