Online Action Recognition with Margin-Based Query Learning
-
- Mori Taketoshi
- Graduate School of Information Science and Technology, the University of Tokyo
-
- Shimosaka Masamichi
- Graduate School of Information Science and Technology, the University of Tokyo
-
- Harada Tatsuya
- Graduate School of Information Science and Technology, the University of Tokyo
-
- Sato Tomomasa
- Graduate School of Information Science and Technology, the University of Tokyo
Bibliographic Information
- Other Title
-
- マージンに基づく問い合わせ学習を用いたオンライン動作認識
- マージン ニ モトヅク トイアワセ ガクシュウ オ モチイタ オンライン ドウサ ニンシキ
Search this article
Abstract
In this paper, we propose an online recognition method for daily actions, such as walking and standing. The proposed method has following characteristics: (1) simultaneous recognition that is able to output multiple action names when human act more than one action, such a situation ashuman is waving hand on standing, (2) modeling action classifiers with kernel methods, (3) effective optimization for the parameters of the recognition system with margin-based query learning. The characteristic (2) unifies the process for modeling and learning the classifiers, and makes us easy to incorporate prior knowledge about action. The characteristic (3) reduces the burden of process for annotating action, which is an inevitable task for supervised learning. The experimental results using real motion capture data show that the proposed margin-based query learning is very effective to achieve high performance of the recognition system with very small sized query and annotation process.
Journal
-
- Journal of the Robotics Society of Japan
-
Journal of the Robotics Society of Japan 24 (7), 861-872, 2006
The Robotics Society of Japan
- Tweet
Details 詳細情報について
-
- CRID
- 1390001204726132096
-
- NII Article ID
- 10020360795
-
- NII Book ID
- AN00141189
-
- ISSN
- 18847145
- 02891824
-
- NDL BIB ID
- 8544278
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed