caa a22 4500 467914974 CHVBK 20180406152859.0 cr unu---uuuuu 170328e20060601xx s 000 0 eng 10.1007/s11263-005-4842-z doi (NATIONALLICENCE)springer-10.1007/s11263-005-4842-z Feature-Based Sequence-to-Sequence Matching [Elektronische Daten] [Yaron Caspi, Denis Simakov, Michal Irani] This paper studies the problem of matching two unsynchronized video sequences of the same dynamic scene, recorded by different stationary uncalibrated video cameras. The matching is done both in time and in space, where the spatial matching can be modeled by a homography (for 2D scenarios) or by a fundamental matrix (for 3D scenarios). Our approach is based on matching space-time trajectories of moving objects, in contrast to matching interest points (e.g., corners), as done in regular feature-based image-to-image matching techniques. The sequences are matched in space and time by enforcing consistent matching of all points along corresponding space-time trajectories. By exploiting the dynamic properties of these space-time trajectories, we obtain sub-frame temporal correspondence (synchronization) between the two video sequences. Furthermore, using trajectories rather than feature-points significantly reduces the combinatorial complexity of the spatial point-matching problem when the search space is large. This benefit allows for matching information across sensors in situations which are extremely difficult when only image-to-image matching is used, including: (a) matching under large scale (zoom) differences, (b) very wide base-line matching, and (c) matching across different sensing modalities (e.g., IR and visible-light cameras). We show examples of recovering homographies and fundamental matrices under such conditions. Springer Science + Business Media, LLC., 2006 sequence-to-sequence matching nationallicence alignment in space and time nationallicence dynamic information nationallicence multi-sensor alignment nationallicence wide base-line matching nationallicence trajectory matching nationallicence Caspi Yaron Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut Simakov Denis Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut Irani Michal Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut International Journal of Computer Vision Kluwer Academic Publishers 68/1(2006-06-01), 53-64 0920-5691 68:1<53 2006 68 11263 https://doi.org/10.1007/s11263-005-4842-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11263-005-4842-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Caspi Yaron Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut NATIONALLICENCE 700 1- Simakov Denis Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut NATIONALLICENCE 700 1- Irani Michal Dept. of Computer Science and Applied Math, The Weizmann Institute of Science, 76100, Rehovot, Israel aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 68/1(2006-06-01), 53-64 0920-5691 68:1<53 2006 68 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer