A Method for Associating Patterns of Motion in Events from Video: A Case Study

Author

Bourbakis, Nikolaos ; Bebis, George

Author_Institution

Wright State Univ.

fYear

2006

fDate

Nov. 2006

Firstpage

187

Lastpage

196

Abstract

Representing, associating, interpreting and learning behavioral patterns and rules from observation is always a challenging research problem for cognitive systems and human computer interaction. This problem becomes more difficult in complex environments with many unexpected behavioral patterns from objects, or cells, or individuals or small group of people acting under certain plans at the same time in different locations. This paper targets the development of a novel synergistic methodology for automatically monitoring, representing, associating and interpreting behavioral patterns and activities, and learning rules from complex environments using videos

Keywords

behavioural sciences computing; image classification; image motion analysis; video signal processing; behavioral pattern; cognitive system; human computer interaction; motion pattern; synergistic methodology; video; Bayesian methods; Cameras; Computer aided software engineering; Hidden Markov models; Humans; Image recognition; Layout; Pattern recognition; Stochastic processes; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on

Conference_Location

Arlington, VA

ISSN

1082-3409

Print_ISBN

0-7695-2728-0

Type

conf

DOI

10.1109/ICTAI.2006.16

Filename

4031897