Motion synchrony, i.e., the coordinated motion of a group of individuals, is an interesting phenomenon in nature or daily life. Fish swim in schools, birds fly in flocks, soldiers march in platoons, etc. Our goal is to detect motion synchrony that may be present in the video data, and to track the group of moving objects as a whole. This opens the door to novel algorithms and applications. To this end, we model individual motions as video tubes in space-time, define motion synchrony by the geometric relation among video tubes, and track a whole set of tubes by dynamic programming. The resulting algorithm is highly efficient in practice. Given a video clip of T frames of resolution XxY, we show that finding the K spatially correlated video tubes and determining the presence of synchrony can be solved optimally in O(XYTK) time. Preliminary experiments show that our method is both effective and efficient. Typical running times are 30 - 100 VGA-resolution frames per second after feature extraction, and the accuracy for the detection of synchrony is more than 90% as evaluated in our annotated data set.
['Ying Zheng', 'Steve Gu', 'Carlo Tomasi']
Detecting motion synchrony by video tubes