The Research And Implementation Of Target Tracking Algorithm Based On Mean-shift And Particle Filter

With the rapid development and maturation of computer networks and multimedia technology, as a new educational mode, E-Learning plays a more and more important role in education. Now the number of people who take education through networks is explosive increasing every year. E-Learning is becoming the global trend in education and training region."Smart Classroom"is an important concept in E-Learning. In smart classroom, teachers can use many high-tech products (such as mouse, keyboard, laser pen, display, touch screen, projection and so on) to teach the students both in the room and out as comfortablely as in traditional classroom. To let students in long-distance feel as natural as they are in a real classroom, it needs the system to track the teacher and broadcast the vivid video about the teacher to students in long distance. After reseach about the moving human detection and tracking, this paper proposes an effective moving human detection and tracking algorithm which based on adaptive background updating and color information. After analyzing the smart classroom's traits, a multimodal fusion algorithm is designed. Based on above algorithms, a real-time moving human detection and tracking system is implemented.The main work in this paper includes:1) Research and realize three widly used motion tracking algorithms: Mixture of Guassian movement background algorithm, particles filter and mean shift. And based on the mass experiment results, we summarize the advantages and disadvantages of each algorithm.2) By studying and realizing these three algoritms, we analyse the advantages and features of these three algorithms. Then we derive a new motion tracking algorithm based on the architecture of particles filter and integrated movement background algorithm and mean shift algorithm. In the new algorithm we use mean shift algorithm in particle transform and use movement background algorithm in initialization of particles, in order to prove the robustness, accuracy and real-time features of motion tracking algorithm.3) Using the above algorithm, a real-time moving human detection and tracking system is implemented. It is running stably and reliably.