Multistrategy fusion using mixture model for moving object detection
In a video surveillance domain, mixture models are used in conjunction with a variety of features and filters to detect and track moving objects. However, these systems do not provide clear performance results at the pixel detection level. In this paper, we apply the mixture model to provide several fusion strategies based on the competitive and cooperative principles of integration which we call OR and AND strategies. In addition, we apply the Dempster-Shafer method to mixture models for object detection. Using two video databases, we show the performance of each fusion strategy using receiver operating characteristic curves.