There are a number of skeletal tracking solutions today that support Intel® RealSense™ depth cameras, including the recently launched cubemos™ Skeleton Tracking SDK. Using depth cameras of any kind allows the skeletal tracking system to disambiguate between overlapping or occluded objects or limbs, as well as making the system more robust to different lighting conditions than a solely 2D camera-based algorithm would. This data can then be used to drive interactive displays, games, VR or AR experiences or any number of other unique integrations, such as displaying your ‘ shadow’ projected on the side of a real car. Once those joints are identified, the software connects them into a humanoid skeleton and tracks their position real time. Some systems can also track hands or specific gestures, though this is not true of all skeletal tracking systems. The cameras differentiate a human from a background, and then identify the position of a number of features or joints, such as shoulders, knees, elbows and hands. Skeletal tracking systems usually use depth cameras for the most robust real time results, but it’s also possible to use 2D cameras with open source software to track skeletons at lower frame rates, for example using Openpose. Similar to the motion capture you may have seen used in Hollywood special effects, but without the need for a special suit or markers on the person. Put simply, skeleton tracking uses sensors, frequently cameras or depth cameras, to track the motion of a human being.

The Microsoft Kinect was one of the earliest consumer examples of skeletal tracking, using the data from human movement to interact with games. Skeletal or Skeleton tracking is a term you may or may not have heard before – it has been around for some time, but in some cases if you have encountered it, you may not have realized the technology behind a unique interactive activity was tracking your skeleton.

Motion tracking camera software