Abstract
We tackle multiple people tracking across multiple non-overlapping surveillance cameras installed in a wide area. Existing methods attempt to track people across cameras by utilizing appearance features and spatio-temporal cues to re-identify people across adjacent cameras. @ However, in relatively wide public areas like a shopping mall, since many people may walk and stay arbitrarily, the spatio-temporal constraint is too strict to reject correct matchings, which results in matching errors. Additionally, appearance features can be severely influenced by illumination conditions and camera viewpoints against people, making it difficult to match tracklets by appearance features. These two issues cause fragmentation of tracking trajectories across cameras. We deal with the former issue by selectively relaxing the spatio-temporal constraint and the latter one by introducing a route cue. We show results on data captured by cameras in a shopping mall, and demonstrate that the accuracy of across-camera tracking can be significantly increased under considered settings.
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Acknowledgement
This work was supported by “R&D Program for Implementation of Anti-Crime and Anti-Terrorism Technologies for a Safe and Secure Society,” Funds for integrated promotion of social system reform and research and development of the Ministry of Education, Culture, Sports, Science and Technology, the Japanese Government.
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Kokura, T., Kawanishi, Y., Mukunoki, M., Minoh, M. (2015). Tracking Pedestrians Across Multiple Cameras via Partial Relaxation of Spatio-Temporal Constraint and Utilization of Route Cue. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9010. Springer, Cham. https://doi.org/10.1007/978-3-319-16634-6_43
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DOI: https://doi.org/10.1007/978-3-319-16634-6_43
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