Study of Robust and Intelligent Surveillance in Visible and Multi-modal Framework

This paper gives a review of current state of the art in the development of robust and intelligent surveillance systems, going beyond traditional vision based framework to more advanced multi-modal framework. The goal of automated surveillance system is to assist the human operator in scene analysis and event classification by automatically detecting the objects and analyzing their behavior using computer vision, pattern recognition and signal processing techniques. This review addresses several advancements made in these fields while bringing out the fact that realizing a practical end to end surveillance system still remains a difficult task due to several challenges faced in a real world scenario. With the advancement in sensor and computing technology, it is now economically and technically feasible to adopt multi-camera and multi-modal framework to meet the need of efficient surveillance system in wide range of security applications like security guard for communities and important buildings, traffic surveillance in cities and military applications. Therefore our review includes significant discussion on multi-modal data fusion approach for robust operation. Finally we conclude with discussion on possible future research directions. Povzetek: Opisane so moderne robustne metode inteligentnega nadzora.