A New Fusion Tracking Method with Unknown Noise

Sun Tao, Qin Lu-Fang, Li Wei, Li Jun, Cao Jie

Abstract


In order to sovle the problem of video target tracking problem, this paper proposed a new kind of particle filter with unknown statistical characteristics of noises. This paper derivates the distribution function of statistical properties in detailed with correlative noise by the establishment model of related noise, and gives the real-time estimation equation of the noise statistical characteristics and the system state. The new algorithm reduced the estimation error effectively and improved the anti-noise ability of the system. Under the improving particle filter framework, we used color and motion edge character as observation model and fused multi features weights through the D-S evidence theory. The experimental results showed that the method proposed in this paper has high precision and strong robustness to target tracking under the complicated conditions.


Keywords


Object tracking; Particle filter; Adaptive filtering; Multi features fusion

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v12.i10.pp7262-7273
Total views : 98 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics