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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/54862

    Title: 3D Skeleton Construction by Multi-View 2D Images and 3D Model Segmentation
    Authors: Chang, Shih-ming;Tsai, Yi-sheng;Hsu, Hui-huang;Li, Kuan-ching
    Contributors: 淡江大學資訊工程學系
    Keywords: 3D skeleton construction;3D object clustering;Speeded Up Robust Features;SURF
    Date: 2011-07-04
    Issue Date: 2011-07-27 11:26:47 (UTC+8)
    Publisher: IEEE Computer Society
    Abstract: In this paper, we proposed method to develop 3D skeleton and 3D object clustering. In 3D skeleton, Firstly,we use multi-view human images and find the feature points between difference angles by Speeded Up Robust Features (SURF) method. Second, we use an effective coordinate transformation method to transform feature points in 3D space. Third, we use improvement K-means algorithm, add three direction, to find the human join
    points and to produce a simple 3D skeleton. In 3D object segmentation, we use Shape Diameter-Function (SDF)method and Gaussian Mixture Model (GMM) to segment regions in 3D model. In SDF method, we use SDF method to compute the SDF value by center of shape information and neighbor of current shape path information. In GMM method, we use GMM method to obtain the scope value of object clustering. Finally, we show results of our method in experiment results, and results show that our method is effective.
    Relation: Proceedings of 2011 Fourth International Conference on Ubi-media Computing, pp.168-173
    DOI: 10.1109/U-MEDIA.2011.48
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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