Human Pose Estimation for Kinect
Kinect for Xbox 360 and Windows makes you the controller by fusing 3D imaging hardware with markerless human-motion capture software. Our group investigates such software. Mixing computer vision, graphics, and machine learning techniques, we look at how to build algorithms that can learn to recognize human poses quickly and reliably.
Images
 Traditional RGB image |
 Image from new depth sensing camera |
 Body parts inferred by our recognition algorithm |
 3D body part position proposals |
People
Publications
- A. Criminisi and J. Shotton, Decision Forests for Computer Vision and Medical Image Analysis, Springer, February 2013.
- N. Pittman, A. Forin, A. Criminisi, J. Shotton, and A. Mahram, Image Segmentation Using Hardware Forest Classifiers, in Intl Symp. on Field-Programmable Custom Computing Machines (FCCM), IEEE, 2013.
- Jonathan Taylor, Jamie Shotton, Toby Sharp, and Andrew Fitzgibbon, The Vitruvian Manifold: Inferring Dense Correspondences for One-Shot Human Pose Estimation, in Proc. CVPR, IEEE, June 2012.
- Jamie Shotton, Ross Girshick, Andrew Fitzgibbon, Toby Sharp, Mat Cook, Mark Finocchio, Richard Moore, Pushmeet Kohli, Antonio Criminisi, Alex Kipman, and Andrew Blake, Efficient Human Pose Estimation from Single Depth Images, in Trans. PAMI, IEEE, 2012.
- Min Sun, Pushmeet Kohli, and Jamie Shotton, Conditional Regression Forests for Human Pose Estimation, in Proc. CVPR, IEEE, 2012.
- Ross Girshick, Jamie Shotton, Pushmeet Kohli, Antonio Criminisi, and Andrew Fitzgibbon, Efficient Regression of General-Activity Human Poses from Depth Images, in ICCV, IEEE, October 2011.
- Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, and Andrew Blake, Real-Time Human Pose Recognition in Parts from a Single Depth Image, in CVPR, IEEE, June 2011.
- Rose Johnson, Kenton O'Hara, Abigail Sellen, Claire Cousins, and Antonio Criminisi, Exploring the Potential for Touchless Interaction in Image Guided Interventional Radiology, in ACM Conference on Computer-Human Interaction (CHI). Honourable Mention Award, ACM Conference on Computer-Human Interaction, 7 May 2011.
- Jamie Shotton, John Winn, Carsten Rother, and Antonio Criminisi, TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context, in Int. Journal of Computer Vision (IJCV), Springer Verlag, January 2009.
- Jamie Shotton, Matthew Johnson, and Roberto Cipolla, Semantic Texton Forests for Image Categorization and Segmentation, in Proc. IEEE CVPR, June 2008.
- Toby Sharp, Implementing Decision Trees and Forests on a GPU, in ECCV (4), Springer, 2008.
Quick Links
Related Press
- Binary Body Double: Microsoft Reveals the Science Behind Project Natal for Xbox 360
Scientific American - Kinect for Xbox 360: The inside story of Microsoft's secret 'Project Natal'
WIRED UK - Key Kinect Technology Devised in Cambridge Lab
Wall St Journal Europe