ASIA unversity:Item 310904400/8698
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90429/105609 (86%)
Visitors : 10286044      Online Users : 112
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version

    Please use this identifier to cite or link to this item:

    Title: 3D registration of human face using evolutionary computation and Kriging interpolation
    Authors: Chang, Yau-Zen;Tsai, Zhi-Ren;Lee, Shih-Tseng
    Contributors: Department of Computer Science and Information Engineering
    Keywords: Calculations;Medical applications;Trees (mathematics);Evolutionary computation;Human face registration;Image-guided therapy;Iterative closest point;Kriging model
    Date: 2008
    Issue Date: 2010-04-07 21:27:28 (UTC+8)
    Publisher: Asia University
    Abstract: This paper proposes a fast and robust 3D human face geometric data registration strategy dedicated for image-guided medical applications. The registration scheme is composed of a coarse transformation stage and a fine-tuning stage. In the first stage, fuzzy c-mean is used to reduce the data amount of template 3D image, and evolutionary computation is implemented to find optimal initial pose for the Iterative Closest Point plus k-dimensional (KD) tree scheme. In the second stage, the huge reference image data are replaced by a Kriging model. The time-consuming search for corresponding points in evaluating the degree of misalignment is substituted by projecting the points in the template image onto the model. To illustrate the validity and applicability of the proposed approach, a problem composed of 174 635 points reference image and an 11 280 points template image is demonstrated. Computational results show that our approach accelerates the registration process from 1361.28 seconds to 432.85 seconds when compared with the conventional ICP plus K-D tree scheme, while the average misalignment reduces from 11.35 mm to 2.33 mm. © International Symposium on Artificial Life and Robotics (ISAROB). 2008.
    Relation: Artificial Life and Robotics 13:242-245
    Appears in Collections:[Department of Computer Science and Information Engineering] Journal Artical

    Files in This Item:

    File Description SizeFormat
    196.doc30KbMicrosoft Word673View/Open

    All items in ASIAIR are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback