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29 May 2013 Visual saliency approach to anomaly detection in an image ensemble
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Abstract
Visual saliency is a bottom-up process that identifies those regions in an image that stand out from their surroundings. We oversegment an image as a collection of “super pixels” (SPs). Each SP is salient if it is different in color from all other SPs and if its most similar SPs are nearby. We test our method on image sequences collected by a vehicle. We consider an SP in a frame as salient if it stands out from all frames in a collection that consists of an ensemble of images from different road segments and a sequence of immediate past frames.
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Anurag Singh, Michael A. Pratt, and Chee-Hung Henry Chu "Visual saliency approach to anomaly detection in an image ensemble", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500T (29 May 2013); https://doi.org/10.1117/12.2017623
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