Representation and learning of visual information for pose recognition

Prasser, D. P. and Wyeth, G. F. (2003). Representation and learning of visual information for pose recognition. In: J. Roberts and G. Wyeth, Proceedings of the 2003 Australasian Conference on Robotics and Automation. Australasian Conference on Robotics and Automation 2003, Brisbane, Australia, (1-8). 1-3 December 2003.


Author Prasser, D. P.
Wyeth, G. F.
Title of paper Representation and learning of visual information for pose recognition
Conference name Australasian Conference on Robotics and Automation 2003
Conference location Brisbane, Australia
Conference dates 1-3 December 2003
Proceedings title Proceedings of the 2003 Australasian Conference on Robotics and Automation
Place of Publication Brisbane, Australia
Publisher Australian Robotics and Automation Association (ARAA)
Publication Year 2003
Sub-type Fully published paper
ISBN 0-9587583-5-2
Editor J. Roberts
G. Wyeth
Start page 1
End page 8
Total pages 8
Collection year 2003
Language eng
Abstract/Summary Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.
Subjects E1
280209 Intelligent Robotics
780199 Other
Q-Index Code E1

 
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Created: Fri, 24 Aug 2007, 02:24:06 EST