I lead the Machine Intelligence and Perception group at Microsoft Research Cambridge. My research is focused at the intersection of computer vision, AI, machine learning, and graphics, with particular emphasis on systems that allow people to interact naturally with computers.
Follow me on Twitter: @JamieDJS.
ICCV 2015 papers: hierarchical sampling optimization for hand pose estimation (YouTube video); high-speed model fitting to raw time of flight image data (YouTube video); survey and comparison of depth-based hand tracking algorithms.
Thrilled to be stepping into a new role, leading the amazing team of researchers and engineers that comprise the Machine Intelligence and Perception group.
New ToG paper on interactive semantic scene labeling now available.
CVPR 2015 papers on exploiting uncertainty in scene coordinate regression and on learning a parametric shape basis for the human hand now available.
Real-time, accurate, robust, and flexible articulated tracking of the human hand.
Memory-efficient generalization of decision trees and forests with improved generalization.
Scene Coordinate Regression Forests
A new approach to 6D camera pose estimation by regression 3D scene coordinates.
Our work on human body part recognition for Kinect.
- Tutorial on Decision Forests and Fields as presented at ICCV 2013.
- 7-Scenes RGB-D camera relocalization dataset now available.
- Decision Forests book including tutorial and software available here.
- For work before I joined MSR, please see my external site.
(In rough reverse chronological order)
- Eduardo Soto
- Arran Topalian
- Benjamin Luff
- David Tan
- Jingjing Shen
- Anna Thomas
- Alina Kuznetsova
- Shubham Tulsiani
- Jan Stühmer
- Sameh Khamis
- Danhang Tang
- Sean Fanello
- Varun Ramakrishna
- Abner Guzman-Rivera
- Julien Valentin
- Richard Stebbing
- Nima Razavi
- Jonathan Taylor
- Gerard Pons-Moll
- Stefan Holzer
- Ross Girshick
- Albert Montillo
- Min Sun
- Richard Newcombe
- Nicolas Heess
- Inmar Givoni
- Brian Amberg
- Zhao Yi
Jamie Shotton leads the Machine Intelligence & Perception group at Microsoft Research Cambridge. He studied Computer Science at the University of Cambridge, where he remained for his PhD in computer vision and machine learning for visual object recognition. He joined Microsoft Research in 2008 where he is now a Principal Researcher. His research focuses at the intersection of computer vision, AI, machine learning, and graphics, with particular emphasis on systems that allow people to interact naturally with computers. He has received multiple Best Paper and Best Demo awards at top academic conferences. His work on machine learning for body part recognition for Kinect was awarded the Royal Academy of Engineering's gold medal MacRobert Award 2011, and he shares Microsoft's Outstanding Technical Achievement Award for 2012 with the Kinect engineering team. In 2014 he received the PAMI Young Researcher Award, and in 2015 the MIT Technology Review Innovator Under 35 Award ("TR35").