Robust moving object detection based on spatio‐temporal confidence relationship

It is still an open problem in the context of complex scenarios like dynamic background and illumination variations, although numerous moving object detection schemes have been demonstrated. Great efforts have been made to develop some probability distribution pixels obey, for which samples are collected from spatial domain and/or temporal domain. However, significant attention has not been paid to the confidence relationship between pixels and its spatio-temporal neighbours in previous works. In this Letter, a confidence relationship model is proposed to complete the moving object detection task in complex environments. Experiments on typical surveillance scenes verify that the proposed algorithm has attractive robustness and high accuracy for illumination variations and dynamic background against state-of-the-art methods.