Yaw Estimation Using Cylindrical and Ellipsoidal Face Models

Abstract

Accurate head yaw estimation is necessary for detecting driver inattention in forward collision warning systems. In this paper, we propose three geometric models under the ellipsoidal framework for accurate head yaw estimation. We present theoretical analysis of the cylindrical and ellipsoidal face models used for yaw angle estimation of head rotation. The relationship between cylindrical, ellipsoidal, and proposed models is derived. We provide error functions for all models. Furthermore, for each model, over/under estimation of angle, zero crossings of error, bounds on yaw angle estimate, and bounds on error are presented. Experimental results of the proposed models on four standard head pose data sets yielded a mean absolute error between 4° and 8° demonstrating the efficacy of the proposed models over the state-of-the-art methods.