Title :
Automatic change detection in an indoor environment
Author :
Al-Khateeb, Hussein ; Petrou, Maria
Author_Institution :
Imperial Coll. London, London, UK
Abstract :
Identifying moving objects from a video sequence is a fundamental task in many computer-vision applications. Background subtraction is a widely used approach for detecting moving objects from static cameras. However, this approach is very sensitive to scene changes due to changes in lighting and movement of background objects, therefore, it should be carefully modeled to be adaptive to any of those changes. This paper proposes a fully adaptive background subtraction method which could automatically detect moving people in different fields of view.
Keywords :
computer vision; image sequences; object detection; automatic change detection; background subtraction; computer vision applications; indoor environment; moving objects; static cameras; video sequence; Cameras; Educational institutions; Filters; Indoor environments; Kernel; Layout; Object detection; Pixel; Robustness; Video sequences;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4244-7029-7
DOI :
10.1109/CVPRW.2010.5543154