Part-based spatio-temporal model for multi-person re-identification

• Published in: Pattern recognition letters Vol. 33; no. 14; pp. 1908 - 1915
• Main Authors: Bedagkar-Gala, A., Shah, Shishir K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.10.2012
• Subjects: Closed-set matching; Open-set matching; Person re-identification; Representative color descriptor; Sparse representation; Closed-set matching; Sparse representation; Representative color descriptor; Person re-identification; Open-set matching
• ISSN: 0167-8655; 1872-7344
• DOI: 10.1016/j.patrec.2011.09.005

► Adaptive spatio-temporal model for re-identification is proposed. ► Model leverages color and facial features. ► Multiple person re-identification as open set matching is studied. ► False acceptance reduction criteria proposed. ► Facial features inclusion improves re-identification performance. In this paper we propose an adaptive part-based spatio-temporal model that characterizes person’s appearance using color and facial features. Face image selection based on low level cues is used to select usable face images to build a face model. Color features that capture the distribution of colors as well as the representative colors are used to build the color model. The model is built over a sequence of frames of an individual and hence captures the characteristic appearance as well as its variations over time. We also address the problem of multiple person re-identification in the absence of calibration data or prior knowledge about the camera layout. Multiple person re-identification is a open set matching problem with a dynamically evolving and open gallery set and an open probe set. Re-identification is posed as a rectangular assignment problem and is solved to find a bijection that minimizes the overall assignment cost. Open and closed set re-identification is tested on 30 videos collected with nine non-overlapping cameras spanning outdoor and indoor areas, with 40 subjects under observation. A false acceptance reduction scheme based on the developed model is also proposed.