Determining 3-D Object Pose Using the Complex Extended Gaussian Image
Abstract
A method based on the extended Gaussian image (EGI) which can be used to determine the pose of a 3-D object is presented. 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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Kang and Ikeuchi. "Determining 3-D Object Pose Using the Complex Extended Gaussian Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139757Markdown
[Kang and Ikeuchi. "Determining 3-D Object Pose Using the Complex Extended Gaussian Image." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/kang1991cvpr-determining/) doi:10.1109/CVPR.1991.139757BibTeX
@inproceedings{kang1991cvpr-determining,
title = {{Determining 3-D Object Pose Using the Complex Extended Gaussian Image}},
author = {Kang, Sing Bing and Ikeuchi, Katsushi},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1991},
pages = {580-585},
doi = {10.1109/CVPR.1991.139757},
url = {https://mlanthology.org/cvpr/1991/kang1991cvpr-determining/}
}