@inproceedings{f5094617e0d64f95899517a97f8394d1,
title = "Object recognition based on three-dimensional model",
abstract = "It is a challenging work to achieve viewpoint independent object recognition. A new efficient method of object recognition based on 3D model is proposed in this paper. Firstly, we obtain multiple 2D projected images of a single 3D model from different directions, and then extract the normalized Fourier Descriptors of the object's edge in the projected images. According to the fact that 2D projection images within limited view range have continuity and similarity, projections can be clustered into the multiple view feature model, leading to an appropriate number of cluster classes and increases the recognition rate. Finally, the SVM classifier is used for recognition. The experiment results show the effectiveness and efficiency of method proposed.",
keywords = "3D model, multiple view feature model, normalized Fourier Descriptor, Object recognition, SVM",
author = "Jun Liang and Yanning Zhang and Zenggang Lin and Zhe Guo and Chao Zhang",
year = "2012",
doi = "10.1007/978-3-642-31919-8\_28",
language = "英语",
isbn = "9783642319181",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "218--225",
booktitle = "Intelligent Science and Intelligent Data Engineering - Second Sino-Foreign-Interchange Workshop, IScIDE 2011, Revised Selected Papers",
note = "2nd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2011 ; Conference date: 23-10-2011 Through 25-10-2011",
}