3D Tracking by Catadioptric Vision Based on Particle Filters

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3D Tracking by Catadioptric Vision Based on Particle Filters
This paper presents a robust tracking system for autonomous robots equipped with omnidirectional cameras. The proposed method uses a 3D shape and color-based object model. This allows to tackle difficulties that arise when the tracked object is placed above the ground plane floor. Tracking under these conditions has two major difficulties: first, observation with omnidirectional sensors largely deforms the target’s shape; second, the object of interest embedded in a dynamic scenario may suffer from occlusion, overlap and ambiguities. To surmount these difficulties, we use a 3D particle filter to represent the target’s state space: position and velocity with respect to the robot. To compute the likelihood of each particle the following features are taken into account: i) image color; ii) mismatch between target’s color and background color. We test the accuracy of the algorithm in a RoboCup Middle Size League scenario, both with static and moving targets.
Matteo Taiana, José António Gaspar,
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Authors Matteo Taiana, José António Gaspar, Jacinto C. Nascimento, Alexandre Bernardino, Pedro U. Lima
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