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Publication Citation: Salient Local 3D Features for 3D Shape Retrieval

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Author(s): Afzal A. Godil; Asim Wagan;
Title: Salient Local 3D Features for 3D Shape Retrieval
Published: April 07, 2011
Abstract: In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.
Conference: IS&T / SPIE 3D Image Processing and Applications
Proceedings: SPIE Symposium Electronic Imaging
Pages: 8 pp.
Location: San Francisco , CA
Dates: January 23-27, 2011
Keywords: 3D model retrieval, voxel grid, non-rigid 3D Model retrieval, bag of words approach, Scale Invariant Feature Transform (SIFT)
Research Areas: Electronic Commerce, Data and Informatics, Data Mining, Information Delivery Systems, Modeling, Software, Information Technology, Imaging