Silhouette-based method for object classification and human action recognition in video
Date
2006Source Title
Lecture Notes in Computer Science
Print ISSN
0302-9743
Electronic ISSN
1611-3349
Publisher
Springer
Volume
3979
Pages
64 - 77
Language
English
Type
ArticleItem Usage Stats
203
views
views
251
downloads
downloads
Abstract
In this paper we present an instance based machine learning algorithm and system for real-time object classification and human action recognition which can help to build intelligent surveillance systems. The proposed method makes use of object silhouettes to classify objects and actions of humans present in a scene monitored by a stationary camera. An adaptive background subtracttion model is used for object segmentation. Template matching based supervised learning method is adopted to classify objects into classes like human, human group and vehicle; and human actions into predefined classes like walking, boxing and kicking by making use of object silhouettes.