Research on the Video Segmentation Method with Integrated Multi-features Based on GMM

Abstract

Video segmentation is a hot issue in the image research field. In the current video segmentation method, the pixel color feature in a frame is only considered. The pertinent problem between adjacent pixels is not taken into account. This paper proposes a video segmentation method based on GMM (Gaussian Mixture Model) modeling, meanwhile a method integrating the neighborhood characteristic of a pixel, such as pixel color and brightness characteristic is considered. The neighbor characteristic of a pixel can be a good solution for the bad segmentation result because of the tiny change in the background. The characteristic of brightness and chromaticity can solve the problem arising from the light and shadow change. In this method, the Gaussian mixture models for each pixel are built firstly. Then the relevant parameters are trained and identified. Combining the neighbor characteristic of pixel, brightness and chromaticity, the video can be segmented. Experiment results show that this method compared with other methods improves the video segmentation results.