Object-Based Surveillance Video Retrieval System with Real-Time Indexing Methodology

This paper presents a novel surveillance video indexing and retrieval system based on object features similarity measurement. The system firstly extracts moving objects from the videos by an efficient motion segmentation method. The fundamental features of each moving object are then extracted and indexed into the database. During retrieval, the system matches the query with the features indexed in the database without re-processing the videos. Video clips which contain the objects with sufficiently high relevance scores are then returned. The

• Type: Conference
• Year: 2007
• Where: ICIAR
• Authors: Jacky S-C. Yuk, Kwan-Yee Kenneth Wong, Ronald H. Y. Chung, K. P. Chow, Francis Y. L. Chin, Kenneth S. H. Tsang
• Keywords: Efficient Motion Segmentation, ICIAR 2007, Image Analysis, Object Features Similarity, Surveillance Video Indexing