Abstract


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Click to download PDF version Click to download BibTeX data Clik to view abstract L. Itti, The Beobot Platform for Embedded Real-Time Neuromorphic Vision, In: Advances in Neural Information Processing Systems, Vol. 15, Hardware Demo Track, (T. G. Dietterich, S. Becker, Z. Ghahramani Ed.), Cambridge, MA:MIT Press, 2003.

Abstract: We demonstrate a new mobile robotics platform designed for the implementation and testing of neuromorphic vision algorithms in unconstrained outdoors environments. It is being developed by a team of undergraduate students with graduate supervision and help. Its distinctive features include significant computational power (four 1.4GHz CPUs with gigabit interconnect), high-speed four-wheel-drive chassis, standard Linux operating system, and a comprehensive toolkit of C++ vision classes. The robot is designed with two major goals in mind: real-time operation of sophisticated neuromorphic vision algorithms, and off-the-shelf components to ensure rapid technological evolvability. A preliminary embedded neuromorphic vision architecture that includes attentional, gist/layout, object recognition, and high-level decision subsystems is showcased (see http://iLab.usc.edu/beobots/ for additional information).

Keywords: Robotics ; Neuromorphic Engineering ; Computational Modeling ; Visual Processing ; Visual Attention

Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Beobots, Scene Understanding, Computer Vision

 

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