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The innovation behind Kinect hinges on advances in skeletal tracking. In skeletal tracking, a human body is represented  by a number of joints representing body parts such as head, neck, shoulders, and arms (see Figure 5a). 4a).  Each joint is represented by its 3D coordinates. The goal is to determine all the 3D parameters of these joints in real time to allow fluent interactivity and with limited computation resources allocated on the Xbox 360 so as not to impact gaming performance. Rather than trying to determine directly the body pose in this high-dimensional space, Jamie Shotton and his team met the challenge by proposing per-pixel, body-part recognition as an intermediate step (see Figure 5b). 4b).  Due to their innovative work, Microsoft honored the Kinect Skeletal Tracking team members with the 2012 Outstanding Technical Achievement Award (www.microsoft.com/about/technicalrecognition/Kinect-Skeletal-Tracking.aspx). Figure 6 5  illustrates the whole pipeline of Kinect skeletal tracking. The first step is to perform per-pixel, body-part classification. The second step is to hypothesize the body joints by finding a global centroid of probability mass (local modes of density) through mean shift. The final stage is to map hypothesized joints to the skeletal joints and fit a skeleton by considering both temporal continuity and prior knowledge from skeletal train data.