Oriented-Filters Based Head Pose Estimation

Abstract

The aim of this study is to elaborate and validate a methodology to automatically assess head orientation with respect to a camera in a video sequence. The proposed method uses relatively stable facial features (upper points of the eyebrows, upper nasolabial-furrow corners and nasal root) that have symmetric properties to recover the face slant and tilt angles. These fiducial points are characterized by a bank of steerable filters. Using the frequency domain, we present an elegant formulation to linearly decompose a Gaussian steerable filter into a set of x, y separable basis Gaussian kernels. A practical scheme to estimate the position of the occasionally occluded nasolabial-furrow facial feature is also proposed. Results show that head motion can be estimated with sufficient precision to obtain the gaze direction without camera calibration or any other particular settings are required for this purpose.