Automatic Combination of Feature Descriptors for Effective 3D Shape Retrieval

  • Biao Leng
  • Zheng Qin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4418)


We focus on improving the effectiveness of content-based 3D shape retrieval. Motivated by retrieval performance of several individual 3D model feature vectors, we propose a novel method, called prior knowledge based automatic weighted combination, to improve the retrieval effectiveness. The method dynamically determines the weighting scheme for different feature vectors based on the prior knowledge. The experimental results show that the proposed method provides significant improvements on retrieval effectiveness of 3D shape search with several measures on a standard 3D database. Compared with two existing combination methods, the prior knowledge weighted combination technique has gained better retrieval effectiveness.


Feature Vector Average Precision Retrieval Performance Weighted Combination Query Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Biao Leng
    • 1
  • Zheng Qin
    • 1
  1. 1.Department of Computer Science & Technology, Tsinghua University, 100084, Beijing, China, School of Software, Tsinghua University, 100084, BeijingChina

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