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Iterative Improvement of Human Pose Classification Using Guide Ontology
https://uec.repo.nii.ac.jp/records/9154
https://uec.repo.nii.ac.jp/records/9154d61e6638-923c-4119-8a7d-ba0d27b4bd5c
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
E99.D_2015EDP7067 (3.3 MB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2019-05-08 | |||||
| タイトル | ||||||
| タイトル | Iterative Improvement of Human Pose Classification Using Guide Ontology | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | ontology | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | semantic web | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | knowledge representation | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| 著者 |
TASHIRO, Kazuhiro
× TASHIRO, Kazuhiro× KAWAMURA, Takahiro× SEI, Yuichi× NAKAGAWA, Hiroyuki× TAHARA, Yasuyuki× OHSUGA, Akihiko |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | 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. | |||||
| 書誌情報 |
en : IEICE Transactions on Information and Systems 巻 E99.D, 号 1, p. 236-247, 発行日 2016-01-01 |
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| 出版者 | ||||||
| 出版者 | The Institute of Electronics, Information and Communication Engineers | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0916-8532 | |||||
| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1587/transinf.2015EDP7067 | |||||
| 権利 | ||||||
| 権利情報 | Copyright © 2016 IEICE | |||||
| 関連サイト | ||||||
| 識別子タイプ | URI | |||||
| 関連識別子 | http://search.ieice.org/index.html | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
