DMCA
A Bayesian computer vision system for modeling human interactions (2000)
Cached
Download Links
| Venue: | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE |
| Citations: | 538 - 6 self |
BibTeX
@ARTICLE{Oliver00abayesian,
author = {Nuria M. Oliver and Barbara Rosario and Alex P. Pentland},
title = {A Bayesian computer vision system for modeling human interactions},
journal = {IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE},
year = {2000},
volume = {22},
number = {8},
pages = {831--843}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
We describe a real-time computer vision and machine learning system for modeling and recognizing human behaviors in a visual surveillance task [1]. The system is particularly concerned with detecting when interactions between people occur and classifying the type of interaction. Examples of interesting interaction behaviors include following another person, altering one's path to meet another, and so forth. Our system combines top-down with bottom-up information in a closed feedback loop, with both components employing a statistical Bayesian approach [2]. We propose and compare two different state-based learning architectures, namely, HMMs and CHMMs for modeling behaviors and interactions. The CHMM model is shown to work much more efficiently and accurately. Finally, to deal with the problem of limited training data, a synthetic ªAlife-styleº training system is used to develop flexible prior models for recognizing human interactions. We demonstrate the ability to use these a priori models to accurately classify real human behaviors and interactions with no additional tuning or training.
Keyphrases
human interaction bayesian computer vision system limited training data bottom-up information machine learning system flexible prior model human behavior real human behavior priori model different state-based learning architecture statistical bayesian approach visual surveillance task interaction behavior synthetic alife-style training system real-time computer vision additional tuning closed feedback loop chmm model
