Title
A view-based real-time human action recognition system as an interface for human computer interaction
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.
Year
DOI
Venue
2007
10.1007/978-3-540-78566-8_10
VSMM
Keywords
Field
DocType
real-time human action recognition,human computer interaction,multiple person,tracked people,distinct human action,gaussians algorithm,view-based real-time human action,recognition system,motion history image,proposed system,assigning people,system segments blob,high recognition rate,hci,multi layer perceptron,real time,mixture of gaussians
Computer vision,Computer science,Action recognition,View based,Artificial intelligence,Perceptron,Hierarchical database model,Motion History Images,Mixture model
Conference
Volume
ISSN
ISBN
4820
0302-9743
3-540-78565-5
Citations 
PageRank 
References 
6
0.43
6
Authors
4
Name
Order
Citations
PageRank
Jin Choi1101.38
Yong-Il Cho2332.23
Taewoo Han3798.41
Hyun S. Yang428835.12