caa a22 4500 467936811 CHVBK 20180406152959.0 cr unu---uuuuu 170328e20060801xx s 000 0 eng 10.1007/s00138-006-0031-5 doi (NATIONALLICENCE)springer-10.1007/s00138-006-0031-5 A Robust Approach for Structure from Planar Motion by Stereo Image Sequences [Elektronische Daten] [Tai Chen, Yun-Hui Liu] This paper proposes a robust method for recovery of motion and structure from two image sequences taken by stereo cameras undergoing a planar motion. The feature correspondences between images are extracted and refined automatically by the relation of the stereo cameras and the property of the motion. To improve the robustness, an auto-scale random sample consensus (RANSAC) algorithm is adopted in the motion and structure estimation. Unlike other work recovering epipolar geometry, here we use a random sampling algorithm to recover the 2D motion and to exclude the outliers which lie both on and out of the epipolar lines. Further more, the idea of RANSAC is used in structure estimation to exclude the outliers from the image sequence. The contribution of this work is the development of an approach to make structure and motion estimation more robust and efficient so as to be applicable to real applications. With the adoption of the auto-scale technique, the algorithm completely automates the estimation process without any prior information or user's specification of parameters like thresholds. Indoor and outdoor experiments have been done to verify the performance of the algorithm. The results demonstrated that the proposed algorithm is robust and efficient for applications in planar motions. Springer-Verlag, 2006 Planar motion nationallicence Random sampling nationallicence Auto-scale nationallicence Stereo cameras nationallicence Chen Tai Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, People's Republic of China aut Liu Yun-Hui Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, People's Republic of China aut Machine Vision and Applications Springer-Verlag 17/3(2006-08-01), 197-209 0932-8092 17:3<197 2006 17 138 https://doi.org/10.1007/s00138-006-0031-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00138-006-0031-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen Tai Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, People's Republic of China aut NATIONALLICENCE 700 1- Liu Yun-Hui Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, People's Republic of China aut NATIONALLICENCE 773 0- Machine Vision and Applications Springer-Verlag 17/3(2006-08-01), 197-209 0932-8092 17:3<197 2006 17 138 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer