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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Bečanović, V., Hosseiny, R., Indiveri, G. (2005). Object Tracking Using Multiple Neuromorphic Vision Sensors. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds) RoboCup 2004: Robot Soccer World Cup VIII. RoboCup 2004. Lecture Notes in Computer Science(), vol 3276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32256-6_36
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DOI: https://doi.org/10.1007/978-3-540-32256-6_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25046-3
Online ISBN: 978-3-540-32256-6
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