Head Pose Estimation from Passive Stereo Images
We present an algorithm to estimate the 3D pose (location and orientation) of a previously unseen face from low-quality range im- ages. The algorithm generates many pose candidates from a signature to find the nose tip based on local shape, and then evaluates each candidate by computing an error function. Our algorithm incorporates 2D and 3D cues to make the system robust to low-quality range images acquired by passive stereo systems. It handles large pose variations (of 90 yaw and 45 pitch rotation) and facial variations due to expressions or accessories. For a maximally allowed error of 30, the system achieves an accuracy of 83.6%.