Head Orientation Modeling: Geometric Head Pose Estimation using Monocular Camera
Muhammad Sikandar Lal Khan, Shafiq ur Réhman, Zhihan Lv, Haibo Li · 2013
In this paper we propose a simple and novel method for head pose estimation using 3D geometric modeling. Our algorithm initially employs Haar-like features to detect face and facial features area (more precisely eyes). For robust tracking of these regions; it also uses Tracking-Learning-Detection (TLD) frame work in a given video sequence. Based on two human eye-areas, we model a pivot point using distance measure devised by anthropometric statistic and MPEG-4 coding scheme. This simple geometrical approach relies on human facial feature structure on the camera-view plane to estimate yaw, pitch and roll of the human head. The accuracy and effectiveness of our proposed method is reported on live video sequence considering head mounted inertial measurement unit (IMU).