An adaptive wavelet shrinkage based accumulative frame differencing model for motion segmentation
Motion segmentation in real-world scenes is a fundamental component in computer vision. There exists a variety of motion recognition algorithms, each with varying degrees of accuracy and computational complexity. The most widely used techniques, in the case of static cameras, are those based on frame difference. Those methods have a significant weakness when it comes to detect slow moving objects. Therefore, we introduce in this paper a novel approach that aims to improve motion segmentation by proposing an accumulative wavelet based frame differencing technique. Moreover, in the propo