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A robust model-based tracker combining geometrical and color edge information

Antoine Petit, Éric Marchand, Keyvan Kanani

发表年份
2013
引用次数
27

摘要

This paper focuses on the issue of estimating the complete 3D pose of the camera with respect to a potentially textureless object, through model-based tracking. We propose to robustly combine complementary geometrical and color edge-based features in the minimization process, and to integrate a multiple-hypotheses framework in the geometrical edge-based registration phase. In order to deal with complex 3D models, our method takes advantage of GPU acceleration. Promising results, outperforming classical state-of-art approaches, have been obtained for space robotics applications on various real and synthetic image sequences and using satellite mock-ups as targets.

关键词

Artificial intelligenceComputer visionComputer scienceEnhanced Data Rates for GSM EvolutionTracking (education)Process (computing)MinificationRoboticsAccelerationPose

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