Real-time ghost removal for foreground segmentation methods

Among all the challenges for foreground detection, we focus on detection of ghosts caused by the starting or stopping of objects. We propose a fast and effective method for ghost detection that compares the similarity between the edges of the detected foreground objects and those of the current frame based on object-level knowledge of moving objects. Finally we demonstrate the performance of ghost detection algorithm using a series of urban traffic video sequences including car parking and departure which normally cause ghost problems. The performance evaluation results show that the proposed method can detect and reduce ghost objects efficiently, brings little computational load, and no significant side-effect to the surveillance system.