Phase registration of a single quasi-periodic signal using self dynamic time warping
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Unsupervised clustering of people from 'skeleton' data
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
Pattern Recognition Letters
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This paper proposes a method for period-based gait trajectory matching in the eigenspace using phase synchronization for low frame-rate videos. First, a gait period is detected by maximizing the normalized autocorrelation of the gait silhouette sequence for the temporal axis. Next, a gait silhouette sequence is expressed as a trajectory in the eigenspace and the gait phase is synchronized by time stretching and time shifting of the trajectory based on the detected period. In addition, multiple period-based matching results are integrated via statistical procedures for more robust matching in the presence of fluctuations among gait sequences. Results of experiments conducted with 185 subjects to evaluate the performance of the gait verification with various spatial and temporal resolutions, demonstrate the effectiveness of the proposed method.