  Benchmarking methods for 3d hand tracking is still an open problem due to the
difficulty of acquiring ground truth data. We introduce a new dataset and
benchmarking protocol that is insensitive to the accumulative error of other
protocols. To this end, we create testing frame pairs of increasing difficulty
and measure the pose estimation error separately for each of them. This
approach gives new insights and allows to accurately study the performance of
each feature or method without employing a full tracking pipeline. Following
this protocol, we evaluate various directional distances in the context of
silhouette-based 3d hand tracking, expressed as special cases of a generalized
Chamfer distance form. An appropriate parameter setup is proposed for each of
them, and a comparative study reveals the best performing method in this
context.
