1. [Publications](/publications) 2. Robust Model-based 3D Head Pose Estimation # Robust Model-based 3D Head Pose Estimation ![](/sites/default/files/styles/wide/public/pubs/2015-12_Robust-Model-based-3D/ResultsGeneral2.jpg?itok=kgtBkfqq) We introduce a method for accurate three dimensional head pose estimation using a commodity depth camera. We perform pose estimation by registering a morphable face model to the measured depth data, using a combination of particle swarm optimization (PSO) and the iterative closest point (ICP) algorithm, which minimizes a cost function that includes a 3D registration and a 2D overlap term. The pose is estimated on the fly without requiring an explicit initialization or training phase. Our method handles large pose angles and partial occlusions by dynamically adapting to the reliable visible parts of the face. It is robust and generalizes to different depth sensors without modification. On the Biwi Kinect dataset, we achieve best-in-class performance, with average angular errors of 2.1, 2.1 and 2.4 degrees for yaw, pitch, and roll, respectively, and an average translational error of 5.9 mm, while running at 6 fps on a graphics processing unit. ## Authors Gregory P Meyer (UI Urbana-Champaign) [Shalini Gupta](/person/shalini-de-mello) [Iuri Frosio](/person/iuri-frosio) Dikpal Reddy (NVIDIA) [Jan Kautz](/person/jan-kautz) ## Publication Date Tuesday, December 1, 2015 ## Published in [IEEE International Conference on Computer Vision (ICCV) 2015](http://pamitc.org/iccv15/) ## Research Area [Computer Vision](/research-area/computer-vision) ## Uploaded Files [paper.pdf](https://research.nvidia.com/sites/default/files/pubs/2015-12_Robust-Model-based-3D/paper.pdf "Open file in new window")9.94 MB ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .