DocumentCode :
157896
Title :
Information theoretic sensor management for multi-target tracking with a single pan-tilt-zoom camera
Author :
Salvagnini, Pietro ; Pernici, Federico ; Cristani, Matteo ; Lisanti, Giuseppe ; Masi, Iacopo ; Del Bimbo, Alberto ; Murino, Vittorio
Author_Institution :
Pattern Anal. & Comput. Vision, Ist. Italiano di Tecnol., Genoa, Italy
fYear :
2014
fDate :
24-26 March 2014
Firstpage :
893
Lastpage :
900
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.
Keywords :
cameras; information theory; object tracking; target tracking; video surveillance; PTZ camera management framework; camera focal length; camera mechanical constraints; camera pan; camera tilt; information theoretic principles; information theoretic sensor management; maximum information gain; multitarget tracking; next camera pose; occlusions; pedestrian detectors; single pan-tilt-zoom camera; target physical extension; video surveillance camera; Cameras; Computational modeling; Detectors; Entropy; Estimation; Gaussian distribution; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on
Conference_Location :
Steamboat Springs, CO
Type :
conf
DOI :
10.1109/WACV.2014.6836009
Filename :
6836009
Link To Document :
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