3-D object recognition using MEGI model from range data
Description
Description and recognition of objects is the central considerations of research on computer vision. The key issue is how to represent 3D objects on a machine for recognizing them. Researchers of computer vision commonly employ the extended Gaussian image (EGI) model, but it is not able to express concave objects. In this paper, an MEGI(more EGI) model and coefficient of extended spherical correlation have been proposed. The MEGI model is an, extended EGI modeling which is able to represent concave objects. The extended spherical correlation is a measure for recognizing objects using the MEGI model. It has been demonstrated that this model is able to recognize 3D objects, including concave ones, and to distinguish objects using a part of MEGI from range data.
Journal
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- Proceedings of 12th International Conference on Pattern Recognition
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Proceedings of 12th International Conference on Pattern Recognition 2002-12-17
IEEE Comput. Soc. Press