Dynamic appearance model for particle filter based visual tracking
Pattern Recognition
| Hi-index | 0.00 |
This paper is a new attempt to introduce a “Multi-cue ” Particle Filter tracking method. It uses multiple features to facilitate 2D video tracking from a monocular view. The method’s benefits lie in its robustness and speed. Speed is improved by adaptive adjustment of different cues; robustness is implemented by multiple cues. The proposed method is demonstrated on man tracking with a non-tationary camera in unconstrained outdoor environments. Result shows it is speedier and robust again background noise such as cluttered background, occlusion, color distracters and illumination change than conventional PF.