Key frame selection for multi-shot person re-identification

Abstract

Typical person re-identification approaches rely on a single image to model the visual appearance characteristics for each target. The performance of these systems is very limited as they ignore the immense amount of video data produced by the practical surveillance systems. In this paper, we present a novel multi-shot person re-identification approach based on key frame selection. We propose to conduct a global appearance signature by automatically selecting a set of representative appearance images depicting the different body postures from the tar-get’s trajectory. Then, these images will be modeled into a global appearance signature to perform the re-identification task based on set matching strategy. The robustness of our approach is validated on the challenging HDA+ dataset in contrast to the limitations of existing approaches.