Traditionally, video segmentation usually extracts object using low-level features such as color, texture, edge, motion, and optical flow. This paper originally proposes that the connectivity of object motion is an advanced feature of video moving object because it can reflect semantic meanings of object to some extent. And it can be fully represented on cumulated difference image which is the combination of a certain number of interframe difference images. Based on this principle, a novel system is designed to extract initial moving object automatically. The system includes 3 key
innovations: 1) System is applied on cumulated difference image which can make object more prominent than background noise. Object extraction is based on the connectivity of object motion and it can guarantee the integrity of the extracted object while eliminate big background regions which cannot be removed by conventional change detection methods, for example, intense-noise regions and shadow regions that are not connected tightly to object. 2) Video sequence analysis is performed ahead of video segmentation. Proper object extraction methods are adopted according to the characteristics of background noise and object motion. 3) The adaptive threshold is automatically determined on cumulated difference image after acute noises is removed. The threshold determined here is more reasonable. And with it, most noise can be eliminated while small-motion regions of object are preserved. Results show that this system can extract object in different kinds of sequences automatically, promptly and properly. Thus, this system is very suitable for real time video applications.