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Abstract

This paper describes a new method based on the Extended Gaussian Image @GI) which can be used to determine the pose of a 3-D object. In this scheme, the weight associated with each outward surface normal is a complex weight. The normal distance of the surface from the predefined origin is encoded as the phase of the weight while the magnitude of the weight is the visible area of the surface. This approach decouples the orientation and translation determination into two distinct least-squares problems. Experiments involving synthetic data of two polyhedral and two smooth objects as well as real range data of the same smooth objects indicate the feasibility of this method.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Number of pages: 12

Text Reference

Sing Bing Kang and Katsushi Ikeuchi, "Determining 3-D Object Pose Using the Complex Extended Gaussian Image," Proceedings of the 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '91), June, 1991.

BibTeX Reference

@inproceedings{Kang_1991_4288,
   author = "Sing Bing Kang and Katsushi Ikeuchi",
   title = "Determining 3-D Object Pose Using the Complex Extended Gaussian Image",
   booktitle = "Proceedings of the 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '91)",
   month = "June",
   year = "1991",
}

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