A discriminative approach to frame-by-frame head pose tracking
|Title||A discriminative approach to frame-by-frame head pose tracking|
|Publication Type||Conference Paper|
|Year of Publication||2008|
|Authors||Whitehill, J, Movellan, JR|
|Conference Name||8th IEEE International Conference on Automatic Face Gesture Recognition, 2008. FG '08|
|Keywords||accuracy drift, continuous video sequence, controlled illumination condition, discriminative approach, face detection, face recognition, facial appearance, frame-by-frame head pose tracking, Humans, Image analysis, Image databases, Laboratories, Lighting, Magnetic heads, mean square error methods, pose estimation, Robustness, root-mean-square error tracking, System testing, Video sequences|
We present a discriminative approach to frame-by-frame head pose tracking that is robust to a wide range of illuminations and facial appearances and that is inherently immune to accuracy drift. Most previous research on head pose tracking has been validated on test datasets spanning only a small (< 20) subjects under controlled illumination conditions on continuous video sequences. In contrast, the system presented in this paper was both trained and tested on a much larger database, GENKI, spanning tens of thousands of different subjects, illuminations, and geographical locations from images on the Web. Our pose estimator achieves accuracy of 5.82deg, 5.65deg, and 2.96deg root-mean-square (RMS) error for yaw, pitch, and roll, respectively. A set of 4000 images from this dataset, labeled for pose, was collected and released for use by the research community.