Paper
19 May 2011 Bio-inspired 'surprise' for real-time change detection in visual imagery
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David J. Huber and Deepak Khosla "Bio-inspired 'surprise' for real-time change detection in visual imagery", Proc. SPIE 8049, Automatic Target Recognition XXI, 804904 (19 May 2011); https://doi.org/10.1117/12.883585
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CITATIONS
Cited by 2 scholarly publications and 4 patents.
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KEYWORDS
Detection and tracking algorithms

Video

Visualization

Video surveillance

Computing systems

Surveillance

Target detection

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