19 May 2011 Bio-inspired 'surprise' for real-time change detection in visual imagery
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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.
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David J. Huber, Deepak Khosla, "Bio-inspired 'surprise' for real-time change detection in visual imagery", Proc. SPIE 8049, Automatic Target Recognition XXI, 804904 (19 May 2011); doi: 10.1117/12.883585; https://doi.org/10.1117/12.883585
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