Title :
Multi-target tracking based on KLD mixture particle filter with radial basis function support
Author :
Madapura, Jayanth ; Li, Baoxin
Author_Institution :
Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ
fDate :
March 31 2008-April 4 2008
Abstract :
The two major difficulties associated with practical real time multi-target tracking are accuracy and speed. A new technique is proposed for multi-target tracking based on multi-modal particle filter with fast tracking capability and improved accuracy. The speed in tracking is achieved by a KLD sampling stage while the accuracy is improved by an additional stage that uses radial basis functions (RBF) for interpolating the sparse particles. Test results of the proposed multi-target tracking approach on both synthetic and real video data demonstrate the improved performance.
Keywords :
particle filtering (numerical methods); radial basis function networks; target tracking; KLD mixture; Kullback-Leibler divergence mixture; multimodal particle filter; multitarget tracking; radial basis function support; real video data; sparse particle interpolation; Computer science; Distributed computing; Particle filters; Particle tracking; Sampling methods; State estimation; Target tracking; Testing; KLD Sampling; Kullback-Leibler Divergence; Mixture Particle Filter; Radial Basis Functions;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4517712
