A Probabilistic Observation Model for Stereo Vision Systems: Application to Particle Filter-Based Mapping and Localization

Authors:
Francisco Angel Moreno;Jose Luis Blanco;Javier Gonzalez
Affiliations:
System Engineering and Automation Department, University of Malaga, Spain;System Engineering and Automation Department, University of Malaga, Spain;System Engineering and Automation Department, University of Malaga, Spain
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Year:
2007

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Abstract

In this paper we propose a probabilistic observation model for stereo vision systems which avoids explicit data association between observations and the map by marginalizing the observation likelihood over all the possible associations. We define observations as sets of landmarks composed of their 3D locations, assumed to be normally distributed, and their SIFT descriptors. Our model has been integrated into a particle filter to test its performance in map building and global localization, as illustrated by experiments with a real robot.