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Democratic Integration: Self-Organized Integration of Adaptive Cues

Deptartment of Computer Science, University of Rochester, Rochester, NY, 14627, U.S.A.

Christoph von der Malsburg

Institut für Neuroinformatik, Ruhr-Universität Bochum, Bochum, Germany, and Laboratory for Computational and Biological Vision, University of Southern California, Los Angeles, CA, U.S.A.

Sensory integration or sensor fusion—the integration of information from different modalities, cues, or sensors—is among the most fundamental problems of perception in biological and artificial systems. We propose a new architecture for adaptively integrating different cues in a self-organized manner. In Democratic Integration different cues agree on a result, and each cue adapts toward the result agreed on. In particular, discordant cues are quickly suppressed and recalibrated, while cues having been consistent with the result in the recent past are given a higher weight in the future. The architecture is tested in a face tracking scenario. Experiments show its robustness with respect to sudden changes in the environment as long as the changes disrupt only a minority of cues at the same time, although all cues may be disrupted at one time or another.

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				X. Tang and C. v. d. Malsburg Figure-Ground Separation by Cue Integration Neural Comput., June 1, 2008; 20(6): 1452 - 1472. [Abstract] [Full Text] [PDF]