Automatic multiple target tracking with pan-tilt-zoom (PTZ) cameras is a hard task, with few approaches in the literature, most of them proposing simplistic scenarios. In this paper, we present a PTZ camera management framework which lies on information theoretic principles: at each time step, the next camera pose (pan, tilt, focal length) is chosen, according to a policy which ensures maximum information gain. The formulation takes into account occlusions, physical extension of targets, realistic pedestrian detectors and the mechanical constraints of the camera. Convincing comparative results on synthetic data, realistic simulations and the implementation on a real video surveillance camera validate the effectiveness of the proposed method.

Information theoretic sensor management for multi-target tracking with a single pan-tilt-zoom camera / P. Salvagnini;F. Pernici;M. Cristani;G. Lisanti;I. Masi;A. Del Bimbo;V. Murino. - ELETTRONICO. - (2014), pp. 893-900. (Intervento presentato al convegno IEEE Winter Conference on Applications of Computer Vision nel 2014) [10.1109/WACV.2014.6836009].

Information theoretic sensor management for multi-target tracking with a single pan-tilt-zoom camera

PERNICI, FEDERICO;LISANTI, GIUSEPPE;MASI, IACOPO;DEL BIMBO, ALBERTO;
2014

Abstract

Automatic multiple target tracking with pan-tilt-zoom (PTZ) cameras is a hard task, with few approaches in the literature, most of them proposing simplistic scenarios. In this paper, we present a PTZ camera management framework which lies on information theoretic principles: at each time step, the next camera pose (pan, tilt, focal length) is chosen, according to a policy which ensures maximum information gain. The formulation takes into account occlusions, physical extension of targets, realistic pedestrian detectors and the mechanical constraints of the camera. Convincing comparative results on synthetic data, realistic simulations and the implementation on a real video surveillance camera validate the effectiveness of the proposed method.
2014
IEEE Winter Conference on Applications of Computer Vision
IEEE Winter Conference on Applications of Computer Vision
2014
P. Salvagnini;F. Pernici;M. Cristani;G. Lisanti;I. Masi;A. Del Bimbo;V. Murino
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/913731
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