Iterative Improvement of Human Pose Classification Using Guide Ontology

• TASHIRO Kazuhiro

  Graduate School of Information System, The University of Electro-Communications

• KAWAMURA Takahiro

  Graduate School of Information System, The University of Electro-Communications Department of Information Planning, Japan Science and Technology Agency

• SEI Yuichi

  Graduate School of Information System, The University of Electro-Communications

• NAKAGAWA Hiroyuki

  Graduate School of Information Science and Technology, Osaka University

• TAHARA Yasuyuki

  Graduate School of Information System, The University of Electro-Communications

• OHSUGA Akihiko

  Graduate School of Information System, The University of Electro-Communications

抄録

The objective of this paper is to recognize and classify the poses of idols in still images on the web. The poses found in Japanese idol photos are often complicated and their classification is highly challenging. Although advances in computer vision research have made huge contributions to image recognition, it is not enough to estimate human poses accurately. We thus propose a method that refines result of human pose estimation by Pose Guide Ontology (PGO) and a set of energy functions. PGO, which we introduce in this paper, contains useful background knowledge, such as semantic hierarchies and constraints related to the positional relationship between body parts. Energy functions compute the right positions of body parts based on knowledge of the human body. Through experiments, we also refine PGO iteratively for further improvement of classification accuracy. We demonstrate pose classification into 8 classes on a dataset containing 400 idol images on the web. Result of experiments shows the efficiency of PGO and the energy functions; the F-measure of classification is 15% higher than the non-refined results. In addition to this, we confirm the validity of the energy functions.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E99.D (1), 236-247, 2016

  一般社団法人 電子情報通信学会

キーワード

• ontology
• semantic web
• knowledge representation

詳細情報

• CRID: 1390001204378493824
• NII論文ID: 130005116170
• DOI: 10.1587/transinf.2015edp7067
• ISSN: 17451361
• ISSN: 09168532
• Web Site: http://id.nii.ac.jp/1438/00009096/
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E99.D/1/E99.D_2015EDP7067/_pdf
• 本文言語コード: en
• データソース種別:
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  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可