Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 127-131.doi: 10.11896/jsjkx.200800035

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Three-dimensional Target Recognition Method Based on Pair Point Feature and HierarchicalComplete-linkage Clustering

YUAN Xiao-lei, YUE Xiao-feng, FANG Bo, MA Guo-yuan   

  1. College of Mechanical and Electrical Engineering,Changchun University of Technology,Changchun 130012,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:YUAN Xiao-lei,born in 1994,postgra-duate.Her main research interests include machine vision and intelligent detection.
    YUE Xiao-feng,born in 1971,professor,Ph.D supervisor.His main research interests include machine vision and intelligent detection.
  • Supported by:
    Industrial Technology Research and Development Special Project of Jilin Provincial Development and Reform Commission(2020C018-3).

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Abstract: Aiming at the problem of low efficiency and easy to be disturbed in 3D target recognition algorithm based on original point pair features,a hierarchical compete-linkage clustering algorithm is proposed to identify 3D targets.The global model description is constructed by using all the point pair features on the model.In the two-dimensional space of the local coordinates,the candidate pose is screened by the voting scheme and the hierarchical complete link clustering algorithm to obtain the optimal pose.Experimental results on the UWA dataset show that compared with the original point pair feature algorithm,the proposed hierarchical compete-linkage clustering algorithm has a certain degree of improvement in recognition rate and efficiency compared with the point pair feature algorithm,and the proposed method is practical and effective.

Key words: Hierarchical complete-linkage clustering, Object recognition, Point pair feature, Voting scheme

CLC Number: 

  • TP391.41
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