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