Dynamic Node Collaboration for Mobile Target Tracking in Wireless

Camera Sensor NetworksLiang Liu†,‡, Xi Zhang†, and Huadong Ma‡

† Networking and Information System LaboratoryDepartment 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

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

Introduction

• 2 advantages of camera tracking1. Most informative sensor 2. High-level analysis using image processing• 2 characteristics of camera tracking 1. Cooperative localization algorithm2. Forming a dynamic cluster2. Forming a dynamic cluster

1) Electing of cluster head(CH) 2) Selecting of cluster members(Cm)

Introduction1) Electing of cluster head (CH)2) Selecting of cluster members(Cm)1) Electing of cluster head (CH)

- SMC based tracking procedure2) Selecting of cluster members(Cm)- Optimization-based algorithm

(considering about accuracy and energy consumption)

Motion model of the target

Target location

Target velocity

Sensing model of camera sensors

Li: Location of camerasr: Radius of sensingVi: unit vector of Alpha: offset angle

Sensing model of camera sensors

Background Subtraction

Sensing model of camera sensors

Target tracking by SMC

• Tracking problem consists– Posterior function– Estimating location by expectation

• At t-1, we’ve known

Target tracking by SMC

Posterior function updating

Estimating location by expectation

Dynamic Node Collaboration

Motion Model of Target

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

Simulation Results(Accuracy)

Simulation Results(Energy)