A Novel Square-Root Cubature Information Weighted Consensus Filter Algorithm for Multi-Target Tracking in Distributed Camera Networks

Sensors

Yanming Chen¹  Qingjie Zhao² 

[1] Beijing Key Laboratory of Intelligence Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China; E-Mail

关键词: cubature Kalman filter;    information filter;    consensus algorithm;    multi-target tracking;    distributed camera networks;   

DOI  :  10.3390/s150510526

来源: mdpi

【 摘 要 】

This paper deals with the problem of multi-target tracking in a distributed camera network using the square-root cubature information filter (SCIF). SCIF is an efficient and robust nonlinear filter for multi-sensor data fusion. In camera networks, multiple cameras are arranged in a dispersed manner to cover a large area, and the target may appear in the blind area due to the limited field of view (FOV). Besides, each camera might receive noisy measurements. To overcome these problems, this paper proposes a novel multi-target square-root cubature information weighted consensus filter (MTSCF), which reduces the effect of clutter or spurious measurements using joint probabilistic data association (JPDA) and proper weights on the information matrix and information vector. The simulation results show that the proposed algorithm can efficiently track multiple targets in camera networks and is obviously better in terms of accuracy and stability than conventional multi-target tracking algorithms.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.