Head Pose Estimation from Passive Stereo Images

We present art algorithm to estimate the 3D pose (location and orientation) of a previously unseen face from low-quality range images. The algorithm generates many pose candidates from a signature to filled the nose tip based on local shape, and then evaluates each candidate by computing all 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 degrees yaw and +/- 45 degrees 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%.