Robust Non-rigid Point Set Registration Based on Global and Local Mixture Structural Feature

被引:1
|
作者
Cai, Changkai [1 ]
Zhu, Hao [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing 400065, Peoples R China
基金
中国国家自然科学基金;
关键词
non-rigid point set registration; mixture structural feature; correspondence estimation; space transformation; ALGORITHM;
D O I
10.1109/CAC51589.2020.9326838
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a mixture structural feature based non-rigid point set registration algorithm, this algorithm mainly contains correspondence estimation and space transformation. In the step of correspondence estimation, Euclidean distance and angle based global and local structural features are used to describe structural difference between two point sets. Then the global and local structural features are combined to construct a cost function, which provides the correspondence by minimizing structural difference using a linear assignment method. In the step of space transformation, a thin plate spline function is used to solves space transformation problem of the source point set. The performances of the proposed algorithm are verified by simulation data and real data, and compare with four classical algorithms where proposed algorithm achieves the best alignment in most cases.
引用
收藏
页码:2452 / 2457
页数:6
相关论文
共 50 条
  • [1] A robust global and local mixture distance based non-rigid point set registration
    Yang, Yang
    Ong, Sim Heng
    Foong, Kelvin Weng Chiong
    [J]. PATTERN RECOGNITION, 2015, 48 (01) : 156 - 173
  • [2] Robust non-rigid point set registration method based on asymmetric Gaussian and structural feature
    Dou, Jun
    Niu, Dongmei
    Feng, Zhiquan
    Zhao, Xiuyang
    [J]. IET COMPUTER VISION, 2018, 12 (06) : 806 - 816
  • [3] Non-rigid point set registration using dual-feature finite mixture model and global-local structural preservation
    Zhang, Su
    Yang, Kun
    Yang, Yang
    Luo, Yi
    Wei, Ziquan
    [J]. PATTERN RECOGNITION, 2018, 80 : 183 - 195
  • [4] Non-rigid point set registration via global and local constraints
    Yang, Changcai
    Zhang, Meifang
    Zhang, Zejun
    Wei, Lifang
    Chen, Riqing
    Zhou, Huabing
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (24) : 31607 - 31625
  • [5] Non-Rigid Point Set Registration by Preserving Global and Local Structures
    Ma, Jiayi
    Zhao, Ji
    Yuille, Alan L.
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 25 (01) : 53 - 64
  • [6] A robust non-rigid point set registration algorithm using both local and global constraints
    Chen, Qing-Yan
    Feng, Da-Zheng
    Hu, Hao-Shuang
    [J]. VISUAL COMPUTER, 2023, 39 (03): : 1217 - 1234
  • [7] A robust non-rigid point set registration algorithm using both local and global constraints
    Qing-Yan Chen
    Da-Zheng Feng
    Hao-Shuang Hu
    [J]. The Visual Computer, 2023, 39 : 1217 - 1234
  • [8] Non-rigid point set registration via global and local constraints
    Changcai Yang
    Meifang Zhang
    Zejun Zhang
    Lifang Wei
    Riqing Chen
    Huabing Zhou
    [J]. Multimedia Tools and Applications, 2018, 77 : 31607 - 31625
  • [9] Non-rigid point set registration based on Gaussian mixture model with integrated feature divergence
    Tang, Chuyu
    Wang, Hao
    Chen, Genliang
    Xu, Shaoqiu
    [J]. ROBOTIC INTELLIGENCE AND AUTOMATION, 2024, 44 (02): : 287 - 305
  • [10] Robust non-rigid point registration based on feature-dependant finite mixture model
    Sang, Qiang
    Zhang, Jian-Zhou
    Yu, Zeyun
    [J]. PATTERN RECOGNITION LETTERS, 2013, 34 (13) : 1557 - 1565