Real-Time Segmentation And Tracking Of Moving Objects In Video Sequences

Robust segmentation and tracking is an active field of computer vision. The aid of computer vision make computer have the ability of learning about surrounding information. There is more useful information in motion sequences than static images. Segmentation of moving objects is to find differential objects in motion sequences and track them. This study is important, because it is the base of video retrieving based on content or video coding based on objects and so on. Object tracking is a new research topic with the developing of digital video technology. It has been generally used in military and civil.In this paper there are two studying points: one is to study how to segment objects in video sequences, the other is how to make real-time objects tracking.We can find out motion objects by changing detection in static background scenes. In this paper I bring forward two methods for segmentation and compare them with two traditional methods. At last, I use morphological approach to improve segmental quality.Real-time tracking of moving object is the emphasis of this paper. Based on Mean Shift algorithm I propose Dynamical Mean Shift algorithm. In this paper,I use DMSA to track face in video sequences which combines a probability distribution image of flesh color. In the end of this paper, DMSA's tracking accuracy, tolerance to noise, distractors and performance are studied.