PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Insect-inspired estimation of egomotion
Matthias Franz, J. S. Chahl and H. G. Krapp
Neural Computation Volume 16, Number 11, pp. 2245-2260, 2004.

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.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
ID Code:371
Deposited By:Matthias Franz
Deposited On:18 December 2004