Target Tracking and Posture Estimation of 3D Objects by Using Particle Filter and Parametric Eigenspace Method.
Masayuki Obata, Takeshi Nishida, Hidekazu Miyagawa, Fujio Ohkawa · 2007
Abstract In this research, we propose a method executing the particle lter (PF) and the para-metric eigenspace method (PEM) simultaneously. Namely, the PEM is used as a re-sampling method of the PF. Since the PEM is executed at the same frequency as the number of parti-cles, high-speed execution of the proposed method is possible. Moreover, since the posture of the ob-ject can be estimated by using PEM, the position of the moving target object at the next time frame can be estimated in high accuracy. We apply the method to the real vision image, and examine the eectiveness and the performance.