Paper Title
A Novel Framework for Mining Suspicious Activities in Surveillance Videos

The advancement of video surveillance systems have recently captured the interest of both research and industrial worlds due to the growing techniques of analytics in the security domain. The video analytics extracts useful information for protecting unlawful events and providing high level security. The application of data mining techniques detects of unusual or suspicious events in prerecorded and real time video-surveillance sequences. There are lot of solution framework exists those are tend to be highly domain specific. This paper presents a generic framework for mining the suspicious events in surveillance video. It also discusses about the efficient video pre-processing techniques, moving object detection and segmentation, object tracking and research issues and applications of intelligent video surveillance system. Keywords - Suspicious event detection; Moving object segmentation; Object tracking; Video Analysis; Event mining;