A view-based real-time human action recognition system as an interface for human computer interaction

Authors:
Jin Choi;Yong-Il Cho;Taewoo Han;Hyun S. Yang
Affiliations:
AIM Lab., Computer Science Dept., KAIST, Daejeon, South Korea;AIM Lab., Computer Science Dept., KAIST, Daejeon, South Korea;Dept. of Game & Multimedia, Woo-song University, Daejeon, South Korea;AIM Lab., Computer Science Dept., KAIST, Daejeon, South Korea
Venue:
VSMM'07 Proceedings of the 13th international conference on Virtual systems and multimedia
Year:
2007

Citing 4
Cited 1

Human motion analysis: a review

Computer Vision and Image Understanding
The Recognition of Human Movement Using Temporal Templates

IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Multiple Objects through Occlusions

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Object tracking: A survey

ACM Computing Surveys (CSUR)

Human behavior classification by analyzing periodic motions

Frontiers of Computer Science in China

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a real-time human action recognition system that can track multiple persons and recognize distinct human actions through image sequences acquired from a single fixed camera. In particular, when given an image, the system segments blobs by using the Mixture of Gaussians algorithm with a hierarchical data structure. In addition, the system tracks people by estimating the state to which each blob belongs and assigning people according to its state. We then make motion history images for tracked people and recognize actions by using a multi-layer perceptron. The results confirm that we achieved a high recognition rate for the five actions of walking, running, sitting, standing, and falling though each subject performed each action in a slightly different manner. The results also confirm that the proposed system can cope in real time with multiple persons.