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Re-identification of Pedestrians in Crowds Using Dynamic Time Warping
Damien Simonnet1, Michal Lewandowski1, Sergio A. Velastin1, James Orwell1, and Esin Turkbeyler2
1Digital Imaging Research Centre, Kingston University, Kingston-upon-Thames KT1 2EE, UK
damien.simonnet@kingston.ac.uk
m.lewandowski@kingston.ac.uk
sergio.velastin@ieee.org
j.orwell@kingston.ac.uk
2Roke Manor Research, Romsey, Hampshire SO51 0ZN, UK
esin.turkbeyler@roke.co.uk
Abstract. This paper presents a new tracking algorithm to solve on-line the ‘Tag and Track’ problem in a crowded scene with a network of CCTV Pan, Tilt and Zoom (PTZ) cameras. The dataset is very challenging as the non-overlapping cameras exhibit pan tilt and zoom motions, both smoothly and abruptly. Therefore a tracking-by-detection approach is combined with a re-identification method based on appearance features to solve the re-acquisition problem between non overlapping camera views and crowds occlusions. However, conventional re-identification techniques of multi target trackers, which consist of learning an online appearance model to differentiate the target of interest from other people in the scene, are not suitable for this scenario because the tagged pedestrian moves in an environment where pedestrians walking with them are constantly changing. Therefore, a novel multiple shots re-identification technique is proposed which combines a standard single shot re-identification, based on offline training to recognize humans from different views, with a Dynamic Time Warping (DTW) distance.
LNCS 7583, p. 423 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012