Share on Facebook Tweet on Twitter Share on LinkedIn Share by email
Jamie Shotton

Jamie Shotton
PRINCIPAL RESEARCHER
.

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.

News

Research Highlights

Hand Pose Estimation

Real-time, accurate, robust, and flexible articulated tracking of the human hand.

h

Decision Jungles

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.

Human pose estimation for Kinect

Our work on human body part recognition for Kinect.

         

Resources

Former Interns

(In rough reverse chronological order)

Short Biography

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").