Object tracking using multiple neuromorphic vision sensors

Authors:
Vlatko Bečanović;Ramin Hosseiny;Giacomo Indiveri
Affiliations:
Fraunhofer Institute of Autonomous Intelligent Systems, Sankt Augustin, Germany;Fraunhofer Institute of Autonomous Intelligent Systems, Sankt Augustin, Germany;Fraunhofer Institute of Autonomous Intelligent Systems, Sankt Augustin, Germany
Venue:
RoboCup 2004
Year:
2005

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Abstract

In this paper we show how a combination of multiple neuromorphic vision sensors can achieve the same higher level visual processing tasks as carried out by a conventional vision system. We process the multiple neuromorphic sensory signals with a standard auto-regression method in order to fuse the sensory signals and to achieve higher level vision processing tasks at a very high update rate. We also argue why this result is of great relevance for the application domain of reactive and lightweight mobile robotics, at the hands of a soccer robot, where the fastest sensory-motor feedback loop is imperative for a successful participation in a RoboCup soccer competition.