Title
Discovering Emergent Behaviors from Tracks Using Hierarchical Non-parametric Bayesian Methods
Abstract
In video-surveillance, non-parametric Bayesian approaches based on a Hierarchical Dirichlet Process (HDP) have recently shown their efficiency for modeling crowed scene activities. This paper follows this track by proposing a method for detecting and clustering emergent behaviors across different captures made of numerous unconstrained trajectories. Most HDP applications for crowed scenes (e.g. traffic, pedestrians) are based on flow motion features. In contrast, we propose to tackle the problem by using full individual trajectories. Furthermore, our proposed approach relies on a three-level clustering hierarchical Dirichlet process able with a minimum a priori to hierarchically retrieve behaviors at increasing semantical levels: activity atoms, activities and behaviors. We chose to validate our approach on ant trajectories simulated by a Multi-Agent System (MAS) using an ant colony foraging model. The experimentation results have shown the ability of our approach to discover different emergent behaviors at different scales, which could be associated to observable events such as \"forging\" or \"deploying\" for instance.
Year
DOI
Venue
2014
10.1109/ICPR.2014.380
ICPR
Keywords
Field
DocType
Bayes methods,ant colony optimisation,belief networks,multi-agent systems,pattern clustering,video surveillance,HDP,MAS,ant colony foraging model,crowed scene activities modeling,emergent behavior discovery,emergent behaviors clustering,emergent behaviors detection,hierarchical nonparametric Bayesian methods,hierarchically retrieve behaviors,multiagent system,three-level clustering hierarchical Dirichlet process
Hierarchical Dirichlet process,Computer science,A priori and a posteriori,Multi-agent system,Feature extraction,Artificial intelligence,Cluster analysis,Ant colony,Hidden Markov model,Machine learning,Bayesian probability
Conference
ISSN
Citations 
PageRank 
1051-4651
0
0.34
References 
Authors
9
4
Name
Order
Citations
PageRank
Guillaume Chiron182.27
Petra Gomez-Krämer25711.67
Michel Ménard3383.47
Gomez-Kramer, P.400.34