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Person Tracking in Multi Camera Environment

Our activities focus on real time tracking of multiple people using multiple cameras to observe a space from different viewpoints.

The low-level integration of multiple distant views permits to simultaneously estimate the ground position of multiple persons with sub-meter precision even if they are seen occluded by one or more cameras such as when people move in groups. Main challenges are dealing with persistent occlusion, adaptation to illumination changes, scalability to number of people and monitored area, and optimal camera placement and self-calibration. 

Selected publications:

T. Hu, S. Messelodi, O. Lanz: Dynamic Task Decomposition for Decentralized Object Tracking in Complex Scenes. Computer Vision and Image Understanding - CVIU, Special Issue on Image Understanding for Real-world Distributed Video Networks, Vol. 134, pp. 89-104 (2015)

S. Mutlu, T. Hu, O. Lanz: Learning the scene illumination for color-based people tracking in dynamic environment. International Conference on Image Analysis and Processing - ICIAP, Naples, Italy, 11-13 September 2013

O. Lanz, S. Messelodi: A sampling algorithm for occlusion robust multi target detection. IEEE International Conference on Advanced Video and Signal based Surveillance - AVSS 2009, Genova, Italy, September 2-4, 2009, pp. 349-351

O. Lanz: Approximate Bayesian Multibody Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence - PAMI, Vol. 28, No. 9, pp. 1436-1449

Research topics: