University of Cambridge > > Microsoft Research Cambridge, public talks > Body Part Recognition: Making Kinect Robust

Body Part Recognition: Making Kinect Robust

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

This event may be recorded and made available internally or externally via Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending

Microsoft recently launched Xbox Kinect (, a revolution in gaming where your whole body becomes the controller. Human pose estimation has long been a “grand challenge” of computer vision, and Kinect has been the first product that meets the speed, cost, accuracy, and robustness requirements to take pose estimation out of the lab and into the living room.

In this talk we will discuss some of the challenges of pose estimation and the technology behind Kinect, detailing a new algorithm, body part recognition, which drives Kinect’s skeletal tracking pipeline. Body part recognition uses a classifier to produce an interpretation of pixels coming from the Kinect depth-sensing camera into different parts of the body: head, left hand, right knee, etc. Estimating this pixel-wise classification is extremely efficient in parallel on the GPU . The classifications are then pooled across pixels to produce hypotheses of 3D body joint positions for use by a skeletal tracking algorithm. Our method has been designed to be robust, in two ways in particular. First, we train the system with a vast and highly varied training set of synthetic images to ensure the system works for all ages, body shapes & sizes, clothing and hair styles. Second, the recognition does not rely on any temporal information, and this ensures that the system can initialize from arbitrary poses and prevents catastrophic loss of track, enabling extended gameplay for the first time.

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2024, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity