Video synchronization from human motion using rank constraints

Authors:
Philip A. Tresadern;Ian D. Reid
Affiliations:
University of Manchester, School of Cancer and Imaging Sciences, Imaging Science and Biomedical Engineering, Stopford Building, Oxford Road, Manchester, Greater Manchester M13 9PT, United Kingdom;Active Vision Lab, Robotics Research Group, University of Oxford, Parks Rd, Oxford OX1 3PJ, United Kingdom
Venue:
Computer Vision and Image Understanding
Year:
2009

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Abstract

This paper presents a method of synchronizing video sequences that exploits the non-rigidity of sets of 3D point features (e.g., anatomical joint locations) within the scene. The theory is developed for homography, perspective and affine projection models within a unified rank constraint framework that is computationally cheap. An efficient method is then presented that recovers potential frame correspondences, estimates possible synchronization parameters via the Hough transform and refines these parameters using non-linear optimization methods in order to recover synchronization to sub-frame accuracy, even for sequences of unknown and different frame rates. The method is evaluated quantitatively using synthetic data and demonstrated qualitatively on several real sequences.