ICRA 2011 Paper Abstract

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Paper WeP204.3

Mansur, Al (Osaka University), Makihara, Yasushi (OSAKA University), Yagi, Yasushi (Osaka University)

Action Recognition Using Dynamics Features

Scheduled for presentation during the Regular Sessions "Recognition II" (WeP204), Wednesday, May 11, 2011, 15:55−16:10, Room 3E

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on December 8, 2019

Keywords Recognition

Abstract

In this paper, we propose a method of action recognition using features based on physics model. These dynamics futures are composed of torques from knee and hip joints of both legs and implicitly include the gravity, ground reaction forces and the pose of the remaining body parts. These features are more discriminative than the kinematics features, and they result in a low dimensional representation of a human action which preserves much information of the original high dimensional pose. This low dimensional feature allows us to achieve a good classification performance even with a small training data in a simple classification framework such as HMM. The effectiveness of the proposed method is demonstrated through experiments on the CMU motion capture dataset with various actions.

 

 

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