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Conference Paper

Insect-Inspired Estimation of Self-Motion

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83919

Franz,  MO
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Franz, M. (2002). Insect-Inspired Estimation of Self-Motion. Proc. 2nd Workshop on Biologically Motivated Computer Vision 2002, BMCV 2002, (2525), 171-180.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-DE56-5
Abstract
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. In this study, we examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge about the environment. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates turn out to be less reliable.