Fusion of trajectory clusters for situation assessment

Author

Snidaro, Lauro ; Piciarelli, Claudio ; Foresti, Gian Luca

Author_Institution

Dept. of Math. & Comput. Sci., Udine Univ.

fYear

2006

fDate

10-13 July 2006

Firstpage

1

Lastpage

7

Abstract

In this paper, we address the problem of identifying anomalous events in the context of a multi sensor surveillance system. Targets´ trajectories are analyzed and compared to common patterns of activity represented as clusters of trajectories. Here we extend our previous work to cater for observations provided by multiple cameras observing the same scene. Data fusion is performed within the Dempster-Shafer theory of evidence framework. The proposed approach is validated through experimental results performed in the context of an automatic road traffic monitoring application

Keywords

inference mechanisms; road traffic; sensor fusion; surveillance; uncertainty handling; Dempster-Shafer theory; automatic road traffic monitoring application; data fusion; multiple cameras; multisensor surveillance system; situation assessment; target trajectory clusters fusion; Cameras; Clustering algorithms; Computer science; Layout; Mathematics; Monitoring; Roads; Sensor fusion; Sensor systems; Surveillance; Trajectory clustering; multisensor data fusion; situation assessment; surveillance;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Fusion, 2006 9th International Conference on

Conference_Location

Florence

Print_ISBN

1-4244-0953-5

Electronic_ISBN

0-9721844-6-5

Type

conf

DOI

10.1109/ICIF.2006.301658

Filename

4085944