Real-time 3D model-based tracking: combining edge and texture information

This paper proposes a real-time, robust and efficient 3D model-based tracking algorithm. A nonlinear minimization approach is used to register 2D and 3D cues for monocular 3D tracking. The integration of texture information in a more classical nonlinear edge-based pose computation highly increases t...

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Bibliographic Details
Main Authors: Pressigout, M., Marchand, E.
Format: Conference Proceeding
Language:English
Subjects:
Augmented reality
Biomedical imaging
Least squares methods
Medical robotics
Registers
Robot vision systems
Robustness
Service robots
Video sequences
Visual servoing
Online Access:Request full text
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Summary:This paper proposes a real-time, robust and efficient 3D model-based tracking algorithm. A nonlinear minimization approach is used to register 2D and 3D cues for monocular 3D tracking. The integration of texture information in a more classical nonlinear edge-based pose computation highly increases the reliability of more conventional edge-based 3D tracker. Robustness is enforced by integrating a M-estimator into the minimization process via an iteratively re-weighted least squares implementation. The method presented in this paper has been validated on several video sequences as well as in visual servoing experiments considering various objects. Results show the method to be robust to large motions and textured environments
ISSN:1050-4729
2577-087X
DOI:10.1109/ROBOT.2006.1642113