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Proceedings Paper

Bio-inspired 'surprise' for real-time change detection in visual imagery
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Paper Abstract

This paper describes a fast and robust bio-inspired method for change detection in high-resolution visual imagery. It is based on the computation of surprise, a dynamic analogue to visual saliency or attention, that uses very little processing beyond that of the initial computation of saliency. This is different from prior surprise algorithms, which employ complex statistical models to describe the scene and detect anomalies. This algorithm can detect changes in a busy scene (e.g., a person crawling in bushes or a vehicle moving in a desert) in real-time on typical video frame rates and can be used as a front-end to a larger system that includes object recognition and scene understanding modules that operate on the detected surprising regions.

Paper Details

Date Published: 19 May 2011
PDF: 9 pages
Proc. SPIE 8049, Automatic Target Recognition XXI, 804904 (19 May 2011); doi: 10.1117/12.883585
Show Author Affiliations
David J. Huber, HRL Labs., LLC (United States)
Deepak Khosla, HRL Labs., LLC (United States)

Published in SPIE Proceedings Vol. 8049:
Automatic Target Recognition XXI
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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