期刊名称:International Journal of Computer Science and Network Security
印刷版ISSN:1738-7906
出版年度:2010
卷号:10
期号:3
页码:136-143
出版社:International Journal of Computer Science and Network Security
摘要:Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. We propose an approach based on self organization through artificial neural networks, widely applied in human image processing systems and more generally in cognitive science. The proposed approach can handle scenes containing moving backgrounds, gradual illumination variations and camouflage, has no bootstrapping limitations and achieves robust detection for different types of videos taken with stationary cameras.