1. Dynamic Node Collaboration for Mobile Target Tracking in Wireless Camera Sensor Networks Liang Liu†,‡, Xi Zhang†, and Huadong Ma‡ † Networking and Information System Laboratory Department of Electrical and Computer Engineering Texas A&M University, College Station, TX 77843, USA ‡ Beijing Key Lab of Intelligent Telecomm. Software and Multimedia, Beijing University of Posts and Telecomm., Beijing 100876, China Study group 3/10 Jason

2. Outline Introduction Motion model of the target Sensing model of camera sensors Target tracking by SMC Dynamic Node Collaboration Selection of the Cluster Member Simulation Results

3. Introduction 2 advantages of camera tracking 1. Most informative sensor 2.High-level analysis using image processing 2 characteristics of camera tracking 1. Cooperative localization algorithm 2. Forming a dynamic cluster 1)Electing of cluster head(CH) 2)Selecting of cluster members(Cm)

4. Introduction 1)Electing of cluster head (CH) 2)Selecting of cluster members(Cm) 1)Electing of cluster head (CH) - SMC based tracking procedure 2)Selecting of cluster members(Cm) - Optimization-based algorithm (considering about accuracy and energy consumption)

5. Motion model of the target Target location Target velocity

6. Sensing model of camera sensors Li: Location of cameras r: Radius of sensing Vi: unit vector of Alpha: offset angle

7. Sensing model of camera sensors Background Subtraction

8. Sensing model of camera sensors

9. Target tracking by SMC Tracking problem consists – Posterior function – Estimating location by expectation At t-1, we’ve known

10. Target tracking by SMC Posterior function updating Estimating location by expectation

11. Dynamic Node Collaboration Motion Model of Target

12. Selection of Cluster Member Maximum utility: maximize the localization accuracy under the specified cost Minimum cost: minimize the cost so as to attain a specified accuracy

13. Simulation Results(Accuracy)

14. Simulation Results(Energy)