Abstract:
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Skeleton tracking has multiple applications such as games, virtual reality, motion
capture and more. One of the main challenges of pose detection is to
be able to obtain the best possible quality with a cheap and easy-to-use device.
In this work we propose a physically based method to detect errors and
tracking issues which appear when we use low cost tracking devices such as
Kinect. Therefore, we can correct the animation in order to obtain a smoother
movement.
We have implemented the Newton-Euler Algorithm, which allow us to compute
the internal forces involved in a skeleton. In a common movement, forces
are usually smooth without sudden variations. When the tracking yields poor
results or invalid poses the internal forces become very large with a lot of variation.
This allow us to detect when the tracking system fails and the animation
needs to be inferred through di erent methods.
Finally, once the detection algorithm is set up, we propose the Hermite
interpolation to infer the positions of the joints that the tracking system is not
capable of properly determine. This interpolation method allows to take into
account both position and velocity, producing a smooth transition from valid
portions of the animation to the inferred parts. |