Visual saliency approach to anomaly detection in an image ensemble

Anurag Singh; Michael A. Pratt; Chee-Hung Henry Chu

doi:10.1117/12.2017623

29 May 2013 Visual saliency approach to anomaly detection in an image ensemble

Anurag Singh, Michael A. Pratt, Chee-Hung Henry Chu

Proceedings Volume 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI; 87500T (2013) https://doi.org/10.1117/12.2017623
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

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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