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A Novel Approach for Computing Partial Similarity Between 3D Models

  • Wei Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

Abstract

In this paper, we present our initial solution to partial similarity computation between arbitrary 3D polygon models. The task is considered as the estimation of similarity transformations between the query pattern and target object. Two steps accounting for the scaling and rotation/translation parts are carried out, facilitated by applying EMD (earth mover’s distance) to search the correspondence between focused point sets. In order to reduce the computation complexity involved in the second step, we use K-means algorithm to cluster the vertices of each model. We report our early experiments testing the efficiency of the proposed method on a small database as well as detailed discussions and the outline for the future work.

Keywords

Shape Index Partial Match Shape Representation Query Pattern Partial Similarity 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei Chen
    • 1
  1. 1.State Key Lab of CAD&CGZhejiang University 

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