  We present a novel solution to the problem of 3D tracking of the articulated
motion of human hand(s), possibly in interaction with other objects. The vast
majority of contemporary relevant work capitalizes on depth information
provided by RGBD cameras. In this work, we show that accurate and efficient 3D
hand tracking is possible, even for the case of RGB stereo. A straightforward
approach for solving the problem based on such input would be to first recover
depth and then apply a state of the art depth-based 3D hand tracking method.
Unfortunately, this does not work well in practice because the stereo-based,
dense 3D reconstruction of hands is far less accurate than the one obtained by
RGBD cameras. Our approach bypasses 3D reconstruction and follows a completely
different route: 3D hand tracking is formulated as an optimization problem
whose solution is the hand configuration that maximizes the color consistency
between the two views of the hand. We demonstrate the applicability of our
method for real time tracking of a single hand, of a hand manipulating an
object and of two interacting hands. The method has been evaluated
quantitatively on standard datasets and in comparison to relevant, state of the
art RGBD-based approaches. The obtained results demonstrate that the proposed
stereo-based method performs equally well to its RGBD-based competitors, and in
some cases, it even outperforms them.
