Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Spatio-Temporal Alignment of Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Temporal Synchronization of Video Sequences in Theory and in Practice
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Feature-Based Sequence-to-Sequence Matching
International Journal of Computer Vision
Synchronization of Video Sequences from Free-Moving Cameras
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Event Dynamics Based Temporal Registration
IEEE Transactions on Multimedia
Tri-focal tensor-based multiple video synchronization with subframe optimization
IEEE Transactions on Image Processing
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Warping trajectories for video synchronization
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream
Proceedings of the 10th European Conference on Visual Media Production
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Time synchronization of video sequences in a multicamera system is necessary for successfully analyzing the acquired visual information. Even if synchronization is established, its quality may deteriorate over time due to a variety of reasons, most notably frame dropping. Consequently, synchronization must be actively maintained. This paper presents a method for online synchronization that relies only on the video sequences. We introduce a novel definition of low level temporal signals computed from epipolar lines. The spatial matching of two such temporal signals is given by the fundamental matrix. Thus, no pixel correspondence is required, bypassing the problem of correspondence changes in the presence of motion. The synchronization is determined from registration of the temporal signals. We consider general video data with substantial movement in the scene, for which high level information may be hard to extract from each individual camera (e.g., computing trajectories in crowded scenes). Furthermore, a trivial correspondence between the sequences is not assumed to exist. The method is online and can be used to resynchronize video sequences every few seconds, with only a small delay. Experiments on indoor and outdoor sequences demonstrate the effectiveness of the method.