多視点映像におけるハフ変換に基づく投票処理を用いた人物行動認識と位置推定の同時処理

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2014/05/01

タイトル(英語): Simultaneous Recognition of Human Action and its Location Estimation Based on Multi-view Hough Voting

著者名: 原　健翔（名古屋大学大学院情報科学研究科），平山　高嗣（名古屋大学大学院情報科学研究科），間瀬　健二（名古屋大学大学院情報科学研究科）

著者名(英語): Kensho Hara （Graduate School of Information Science, Nagoya University）, Takatsugu Hirayama （Graduate School of Information Science, Nagoya University）, Kenji Mase （Graduate School of Information Science, Nagoya University）

キーワード: 行動認識，多視点映像，ハフ変換，ランダムフォレスト　　Action Recognition，Multi-view Video，Hough Transform，Random Forests

要約(英語): Remote surveillance of large-scale equipments such as power plants and building complex is important to prevent serious attacks and troubles. Automatic human action recognition can reduce the burdens of the surveillance. Multi-view video is useful for human action recognition, because it provides robustness to the changes of people's appearance by orientation and occlusion. One problem of conventional multi-view action recognition is that it requires both detection and tracking before action recognition. Human pose and motion vary depending on the person's action, and such variances may cause detection and tracking error. To solve this problem, previous work has proposed simultaneous action recognition and location estimation for single-view videos using Hough voting. In this paper, we extend the Hough voting approach to simultaneous multi-view action recognition and location estimation. Our proposed method independently casts votes for the action labels and spatio-temporal reference positions of actions in each view and integrates them using homographical transformations in the multi-view extension. We evaluated our method and confirmed that it achieved high accuracy in action recognition and location estimation. The contribution of this paper is that it enables multi-view action recognition without prior human detection and tracking.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.5 （2014） 特集：機械学習手法に基づく設備診断・監視技術

本誌掲載ページ: 634-642 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/5/134_634/_article/-char/ja/