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  • 标题:Model-based Pose Estimation for Texture-less Objects with Differential Evolution Algorithm
  • 本地全文:下载
  • 作者:Linh Tao ; Linh Tao ; Tinh Nguyen
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2017
  • 卷号:108
  • 页码:1-4
  • DOI:10.1051/matecconf/201710815001
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要: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.
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