UDC 004.93, DOI: 10.2298/CSIS1001231W

3D Point Pattern Matching Based on Spatial Geometric Flexibility

Xiaopeng Wei1, 2, Xiaoyong Fang1, 2, Qiang Zhang2 and Dongsheng Zhou1, 2

  1. School of Mechanical and Engineering, Dalian University of Technology
    Dalian, 116024 China
    xpwei@dlu.edu.cn, paperxyfang@gmail.com
  2. Key Laboratory of Advanced Design and Intelligent Computing (Dalian University)
    Ministry of Education, Dalian, 116622, China
    Zhangq26@126.com

Abstract

We propose a new method for matching two 3D point sets of identical cardinality with global similarity but local non-rigid deformations and distribution errors. This problem arises from marker based optical motion capture (Mocap) systems for facial Mocap data. To establish one-to-one identifications, we introduce a forward 3D point pattern matching (PPM) method based on spatial geometric flexibility, which considers a non-rigid deformation between the two point-sets. First, a model normalization algorithm based on simple rules is presented to normalize the two point-sets into a fixed space. Second, a facial topological structure model is constructed, which is used to preserve spatial information for each FP. Finally, we introduce a Local Deformation Matrix (LDM) to rectify local searching vector to meet the local deformation. Experimental results confirm that this method is applicable for robust 3D point pattern matching of sparse point sets with underlying non-rigid deformation and similar distribution.

Key words

Point pattern matching (PPM), Face model, Spatial geometric flexibility, Topological structure, Motion capture (Mocap), Non-rigid deformation

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS1001231W

Publication information

Volume 7, Issue 1 (February 2010)
Advances in Computer Animation and Digital Entertainment
Year of Publication: 2010
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Wei, X., Fang, X., Zhang, Q., Zhou, D.: 3D Point Pattern Matching Based on Spatial Geometric Flexibility. Computer Science and Information Systems, Vol. 7, No. 1. (2010)