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Towards a practical PTZ face detection and tracking system

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3 Author(s)
Yinghao Cai ; Univ. of Southern California, Los Angeles, CA, USA ; Medioni, G. ; Thang Ba Dinh

We address the problem of automatic face detection and tracking in uncontrolled scenarios using a pan-tilt-zoom (PTZ) network camera, which could prove most helpful in forensic applications. The detected faces are associated with the corresponding people and trajectories. The dynamic nature of real-world scenarios and real-time restrictions complicate our task. Different from previous work which use a mixture of wide angle cameras and PTZ cameras, we explore the limits to what can be expected from a single PTZ camera. The system first detects and tracks pedestrians in zoomed-out mode, then selects, using a scheduler, a person to zoom in to. After zoom in, we come back to wide area mode, and solve the person-to-person, face-to-person and face-to-face data association problems. Extensive experiments in challenging indoor and outdoor uncontrolled conditions demonstrate the effectiveness of the proposed system.

Published in:

Applications of Computer Vision (WACV), 2013 IEEE Workshop on

Date of Conference:

15-17 Jan. 2013