Adaptive Probabilistic Tracking Embedded in a Smart Camera

Authors:
Sven Fleck;Wolfgang Strasser
Affiliations:
WSI/GRIS, University of Tubingen;WSI/GRIS, University of Tubingen
Venue:
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Year:
2005

Citing 0
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Adaptive probabilistic tracking embedded in smart cameras for distributed surveillance in a 3D model

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Autonomous multicamera tracking on embedded smart cameras

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An integrated visualization of a smart camera based distributed surveillance system

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System and software architectures of distributed smart cameras

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A parallel histogram-based particle filter for object tracking on SIMD-based smart cameras

Computer Vision and Image Understanding

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Abstract

Tracking applications based on distributed and embedded sensor networks are emerging today, both in the field of surveillance (airports, lab facilities, train stations, museums, public spots) and industrial vision (visual servoing, factory automation). Traditional centralized approaches offer several drawbacks, due to limited communication bandwidth, computational requirements and thus also limited spatial camera resolution and framerate. In this paper, we present a network-enabled Smart Camera for probabilistic tracking. It is capable of tracking objects adaptively in real-time and offers a very bandwidthconservative approach, as the whole computation is performed embedded in the Smart Camera, and only the tracking results are transmitted which are on a higher level of abstraction.