Head movement during high resolution Positron Emission Tomography brain studies causes blur and artifacts in the images. Therefore, attempts are being made to continuously monitor the pose of the head and correct for this movement. Specifically, our method uses a structured light scanner system to create point clouds representing parts of the patient's face. The movement is estimated by a rigid registration of the point clouds. The registration should be done using a robust algorithm that can handle partial overlap and ideally operate in real time. We present an optimized Iterative Closest Point algorithm that operates at 10 frames per second on partial human face surfaces. © 2011 Springer-Verlag.