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Linear Combinations of Optic Flow Vectors for Estimating Self-Motion: a Real-World Test of a Neural Model

2003

Conference Paper

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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 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 self-motion 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 turn out to be less reliable.

Author(s): Franz, MO. and Chahl, JS.
Book Title: Advances in Neural Information Processing Systems 15
Journal: Advances in Neural Information Processing Systems
Pages: 1319-1326
Year: 2003
Month: October
Day: 0
Editors: Becker, S., S. Thrun and K. Obermayer
Publisher: MIT Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002)
Event Place: Vancouver, BC, Canada

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-02550-7
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{1947,
  title = {Linear Combinations of Optic Flow Vectors for Estimating Self-Motion: a Real-World Test of a Neural Model},
  author = {Franz, MO. and Chahl, JS.},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in Neural Information Processing Systems 15},
  pages = {1319-1326},
  editors = {Becker, S., S. Thrun and K. Obermayer},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = oct,
  year = {2003},
  month_numeric = {10}
}