@inproceedings{670c81a60a6a4efab9f59a6052edd973,
title = "Silhouette-based method for object classification and human action recognition in video",
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.",
author = "Yiǧithan Dedeoǧlu and T{\"o}reyin, \{B. Uǧur\} and Uǧur G{\"u}d{\"u}kbay and \{Enis {\c C}etin\}, A.",
year = "2006",
language = "English",
isbn = "3540342028",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "64--77",
booktitle = "Computer Vision in Human-Computer Interaction - ECCV 2006 Workshop on HCI, Proceedings",
address = "Germany",
note = "ECCV 2006 Workshop on HCI ; Conference date: 13-05-2006 Through 13-05-2006",
}