Biomimetic novelty detection

Lein W. Ma; Harold Szu

doi:10.1117/12.855789

12 April 2010 Biomimetic novelty detection

Lein W. Ma, Harold Szu

Proceedings Volume 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII; 770316 (2010) https://doi.org/10.1117/12.855789
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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.

Citation Download Citation

Lein W. Ma and Harold Szu "Biomimetic novelty detection", Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 770316 (12 April 2010); https://doi.org/10.1117/12.855789

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