Abstract
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.
This work was supported by Fundação para a Ciência e a Tecnologia (ISR/IST pluriannual funding) through the POS-Conhecimento Program that includes FEDER funds. We would like to thank Dr. Luis Montesano and Dr. Alessio Del Bue for the helpful discussions.
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Taiana, M., Gaspar, J., Nascimento, J., Bernardino, A., Lima, P. (2008). 3D Tracking by Catadioptric Vision Based on Particle Filters . In: Visser, U., Ribeiro, F., Ohashi, T., Dellaert, F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science(), vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_7
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DOI: https://doi.org/10.1007/978-3-540-68847-1_7
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