Abstract
This paper presents a method to temporally synchronize two independently moving cameras with overlapping views. Temporal variations between image frames (such as moving objects) are powerful cues for alignment. We first generate pulse images by tracking moving objects and examining the trajectories for changes in speed. We then integrate a rank-based constraint and the pulse-based matching, to derive a robust approximation of spatio-temporal alignment quality for all pairs of frames. By folding both spatial and temporal cues into a single alignment framework, finally, the nonlinear temporal mapping is found using a graph-based approach that supports partial temporal overlap between sequences. We verify the robustness and performance of the proposed approach on several challenging real video sequences. Compared to state-of-the-art techniques, our approach is robust to tracking error and can handle non-rigid scene alignment in complex dynamic scenes.
This work was partially supported by National Natural Science Foundation of China (61272287, 61531014).
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Wang, X., Wang, Q. (2016). Video Synchronization with Trajectory Pulse. In: Zhang, Z., Huang, K. (eds) Intelligent Visual Surveillance. IVS 2016. Communications in Computer and Information Science, vol 664. Springer, Singapore. https://doi.org/10.1007/978-981-10-3476-3_2
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DOI: https://doi.org/10.1007/978-981-10-3476-3_2
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