Proceedings Paper
Visual saliency approach to anomaly detection in an image ensemble| Format | Member Price | Non-Member Price |
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Paper 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.
Paper Details
Date Published: 29 May 2013
PDF: 7 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500T (29 May 2013); doi: 10.1117/12.2017623
Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)
PDF: 7 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500T (29 May 2013); doi: 10.1117/12.2017623
Show Author Affiliations
Anurag Singh, Univ. of Louisiana at Lafayette (United States)
Michael A. Pratt, Univ. of Louisiana at Lafayette (United States)
Michael A. Pratt, Univ. of Louisiana at Lafayette (United States)
Chee-Hung Henry Chu, Univ. of Louisiana at Lafayette (United States)
Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)
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