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Proceedings Paper

Biomimetic novelty detection
Author(s): Lein W. Ma; Harold Szu
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Paper Abstract

In the crowded rain forest, how do animals locate camouflaged prey that resemble the environment, such as walking sticks? Birds will observe the suspected stick over a period of time to determine if its behavior matches that of a tree. If the stick's behavior exceeds normal tree behavior, such as moving faster than the other branches, the bird will determine that it is actually a walking stick and not a tree branch. Once this determination is made, they will prey on the insect. Studying this natural process of novelty detection, present in a variety of animals from birds to turkey vultures, can be beneficial for numerous human applications. The spatiotemporal novelty detector will be developed using self-referencing matched filters to go beyond auto-regression. This algorithm is more than the usual change detector for it will detect a novelty behavior that exceeds its predicted value based on past data, e.g. the bird who identifies a walking stick in the forest. A scalar model is presented; however, the application can be expanded to multiple modalities for more detailed applications. Some of these applications include gas pipeline leak detection, persistent surveillance, and the creation of a smart sensor web.

Paper Details

Date Published: 12 April 2010
PDF: 11 pages
Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 770316 (12 April 2010); doi: 10.1117/12.855789
Show Author Affiliations
Lein W. Ma, Univ. of Wisconsin-Madison (United States)
Harold Szu, US Army RDECOM CERDEC NVESD (United States)


Published in SPIE Proceedings Vol. 7703:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
Harold H. Szu; F. Jack Agee, Editor(s)

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