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Computing Similarity Among 3D Objects Using Dynamic Time Warping

  • A. Angeles-Yreta
  • J. Figueroa-Nazuno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

A new model to compute similarity is presented. The representation of a 3D object is reviewed; sequence of vertices and index of vertices are the basic information about the shape of any 3D object. A linear function called Labeling is introduced to create a new sequence or time series from a 3D object. A method to create randomly 3D objects is also described. Experimental results show viability to compute similarity among 3D objects using the extracted sequences and the Dynamic Time Warping algorithm.

Keywords

Dynamic Time Warping Computing Similarity Random Modification Dynamic Time Warping Distance Warping Path 
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 2005

Authors and Affiliations

  • A. Angeles-Yreta
    • 1
  • J. Figueroa-Nazuno
    • 1
  1. 1.Centro de Investigación en Computación, Instituto Politécnico NacionalUnidad Profesional “Adolfo López Mateos”, ZacatencoMéxico D.F.

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