3D Head Pose Tracking Using a Particle Filter with Nose Template Matching

Abstract

In this paper, we propose a real-time tracking method for driver's head pose in real vehicle environment by using multiple NIR cameras. In order to achieve real-time performance and high-accuracy, 6-DOF of head pose is estimated by a particle filter with restricted state space. Firstly, the 3D position of nose hole is measured by template matching of stereo images. Because nose hole is the most dark area in the captured NIR images, we can robustly detect the position of the nose very precisely. From the 3D position of the nose, we can estimate the head pose as an initial estimate. Then, each hypothesis is updated by prior probability with a constraint of nose position. Thus it can reduce the number of particles with maintained accuracy. The experimental results indicate that this method is effective for head pose tracking.