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Journal Article

Insect-inspired estimation of egomotion

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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;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84025

Krapp,  HG
Former Department Comparative Neurobiology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Franz, M., Chahl, J., & Krapp, H. (2004). Insect-inspired estimation of egomotion. Neural Computation, 16(11), 2245-2260. doi:10.1162/0899766041941899.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-D761-1
Abstract
Tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on the organization principles in tangential neurons can be used to estimate egomotion from the optic flow. We present a theory for the construction of an estimator consisting of a linear combination of optic flow vectors that incorporates prior knowledge both about the distance distribution of the environment, and about the noise and egomotion statistics of the sensor. The 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 are of reasonable quality, albeit less reliable.