Template Matching Method Based on Visual Feature Constraint and Structure Constraint

• LI Zhu

  Tokyo University of Agriculture and Technology

• TOMOTSUNE Kojiro

  Tokyo University of Agriculture and Technology

• TOMIOKA Yoichi

  Tokyo University of Agriculture and Technology

• KITAZAWA Hitoshi

  Tokyo University of Agriculture and Technology

抄録

Template matching for image sequences captured with a moving camera is very important for several applications such as Robot Vision, SLAM, ITS, and video surveillance systems. However, it is difficult to realize accurate template matching using only visual feature information such as HSV histograms, edge histograms, HOG histograms, and SIFT features, because it is affected by several phenomena such as illumination change, viewpoint change, size change, and noise. In order to realize robust tracking, structure information such as the relative position of each part of the object should be considered. In this paper, we propose a method that considers both visual feature information and structure information. Experiments show that the proposed method realizes robust tracking and determine the relationships between object parts in the scenes and those in the template.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E95.D (8), 2105-2115, 2012

  一般社団法人 電子情報通信学会

キーワード

• template matching
• visual feature constraint
• structure constraint
• linear assignment
• genetic algorithm

詳細情報

• CRID: 1390282679354976384
• NII論文ID: 10031126719
• NII書誌ID: AA10826272
• DOI: 10.1587/transinf.e95.d.2105
• BIBCODE: 2012IEITC..95.2125L
• ISSN: 17451361
• ISSN: 09168532
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E95.D/8/E95.D_2105/_pdf
• 本文言語コード: en
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