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Non-rigid 3D Model Retrieval Using Set of Local Statistical Features

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4 Author(s)
Ohkita, Y. ; Univ. of Yamanashi, Yamanashi, Japan ; Ohishi, Y. ; Furuya, T. ; Ohbuchi, R.

Various algorithms for shape-based retrieval of non-rigid 3D models, with invariance to articulation and/or global deformation, have been developed. A majority of these algorithms assumes that 3D models have mathematically well-defined representations, e.g., closed, manifold mesh. These algorithms are thus not applicable to other types of shape models, for example, those defined as polygon soup. This paper proposes a 3D model retrieval algorithm that accepts diverse 3D shape representations and is is able to compare non-rigid 3D models. The algorithm employs a set of hundreds to thousands of 3D, statistical, local features to describe a 3D model. These features are integrated into a feature vector per 3D model by using bag-of-features approach for efficiency in comparing 3D models and for invariance against articulation and global deformation. Experimental evaluation showed that the algorithm performed well for non-rigid 3D model retrieval.

Published in:

Multimedia and Expo Workshops (ICMEW), 2012 IEEE International Conference on

Date of Conference:

9-13 July 2012

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