Model-based pose estimation for texture-less objects with differential evolution algorithm

Linh Tao, Tinh Nguyen, Hiroshi Hasegawa

Research output: Contribution to journalArticle

Abstract

This paper proposes a novel object-Tracking method to estimate three dimensions position of texture-less objects using one camera system and 3D model. The system uses efficient chamfer matching method to calculated distances between 2D edge templates of pose hypotheses with edges from the Canny edge query image. Differential Evolution algorithm uses those distances as inputs to ensure the close optimum results and find the most suitable position of objects. For initialization the exhaustive searching is employed. With the good initialization, a smaller searching space is set to guaranty the online tracking ability. The first results showed the potential of the method in solving object tracking and detection problem.

Original languageEnglish
Article number15001
JournalMATEC Web of Conferences
Volume108
DOIs
Publication statusPublished - 2017 May 31

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ASJC Scopus subject areas

  • Chemistry(all)
  • Engineering(all)
  • Materials Science(all)

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