Authors:
Francisco Alfonso Cano
1
;
José Carlos Castillo
1
;
Juan Serrano-Cuerda
1
and
Antonio Fernández-Caballero
2
Affiliations:
1
Universidad de Castilla-La Mancha, Spain
;
2
Universidad de Castilla-La Mancha and Escuela de Ingenieros Industriales de Albacete, Spain
Keyword(s):
Intelligent surveillance systems, Monitoring architecture, Segmentation, Tracking, Activity analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
Abstract:
Intelligent surveillance systems deal with all aspects of threat detection in a given scene; these range from segmentation to activity interpretation. The proposed architecture is a step towards solving the detection and tracking of suspicious objects as well as the analysis of the activities in the scene. It is important to include
different kinds of sensors for the detection process. Indeed, their mutual advantages enhance the performance provided by each sensor on its own. The results of the multisensory architecture offered in the paper, obtained from testing the proposal on CAVIAR project data sets, are very promising within the three proposed levels,
that is, segmentation based on accumulative computation, tracking based on distance calculation and activity analysis based on finite state automaton.