Title :
Sift-based camera tamper detection for video surveillance
Author :
Hongpeng Yin ; Xuguo Jiao ; Xianke Luo ; Chai Yi
Author_Institution :
Coll. of Autom., Chongqing Univ., Chongqing, China
Abstract :
Keeping the camera long time proper functioning without tamper is the fundamentally requirement of a video surveillance system. Traditional camera tamper detection is applied by surveillance system operators. It´s large human resource consuming and inefficiency. In this paper, a SIFT-based automatic camera tamper detection algorithm for video surveillance is proposed. When camera tamper occurred, the real-time frame will be large changed. Therefore, a Sift feature based decision function is employed to detect camera tamper. The threshold is carefully chosen to reduce false alarms. Several experiments are conducted to demonstrate the effectiveness and robust of the proposed method.
Keywords :
transforms; video surveillance; SIFT feature-based decision function; SIFT-based automatic camera tamper detection algorithm; real-time frame; video surveillance system; Cameras; Equations; Mathematical model; Real-time systems; Standards; Video surveillance; SIFT algorithm; camera tamper; covered camera detection; moved camera detection; video surveillance;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561007