On building omnidirectional image signatures using haar invariant features: application to the localization of robots

Authors:
Cyril Charron;Ouiddad Labbani-Igbida;El Mustapha Mouaddib
Affiliations:
Centre de Robotique, Electrotechnique et Automatique, Université de Picardie Jules Verne, Amiens, France;Centre de Robotique, Electrotechnique et Automatique, Université de Picardie Jules Verne, Amiens, France;Centre de Robotique, Electrotechnique et Automatique, Université de Picardie Jules Verne, Amiens, France
Venue:
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Year:
2006

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Abstract

In this paper, we present a method for producing omnidirectional image signatures that are purposed to localize a mobile robot in an office environment. To solve the problem of perceptual aliasing common to the image based recognition approaches, we choose to build signatures that greatly vary between rooms and slowly vary inside a given room. To do so, an invariant approach has been developed, based on Haar invariant integrals. It takes into account the movements the robot can do in a room and the omni image transformations thus produced. A comparison with existing methods is presented using the Fisher criterion. Our method appears to get significantly better results for place recognition and robot localization, reducing in a positive way the perceptual aliasing.