Synchronization of Independently Moving Cameras via Motion Recovery

Gaspar, Tiago; Oliveira, Paulo; Favaro, Paolo (2016). Synchronization of Independently Moving Cameras via Motion Recovery. SIAM Journal on Imaging Sciences, 9(3), pp. 869-900. SIAM 10.1137/15M1035367

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This work addresses the video synchronization problem, which consists in finding the temporal alignment between sequences of images acquired with unsynchronized cameras. This problem has been addressed before, under the assumptions that the cameras are static or jointly moving and that there are correspondences between the features visible in the different sequences. There are some methods in the literature that managed to drop one of these assumptions, but none of them was successful in getting rid of both assumptions simultaneously. In this work, we introduce a new strategy that synchronizes cameras that are allowed to move freely even when there are no correspondences between the features that are visible in the different sequences. Our approach consists in tracking features on two rigid objects that move independently on the scene and use the relative motion between them as a clue for the synchronization. New synchronization algorithms for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object are also presented. Even though the emphasis of this work is essentially on the theoretical contribution of the proposed methods, rather than on an exhaustive experimental validation, several proof of concept experiments conducted with both real and synthetic data are presented. In the case of static or jointly moving cameras, comparisons with a state-of-the-art approach are also provided.

Item Type:

Journal Article (Review Article)


08 Faculty of Science > Institute of Computer Science (INF) > Computer Vision Group (CVG)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Favaro, Paolo


000 Computer science, knowledge & systems
500 Science > 510 Mathematics








Xiaochen Wang

Date Deposited:

12 Jun 2017 16:42

Last Modified:

12 Jun 2017 16:42

Publisher DOI:





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