  Accurate 3D hand pose estimation plays an important role in Human Machine
Interaction (HMI). In the reality of HMI, joints in fingers stretching out,
especially corresponding fingertips, are much more important than other joints.
We propose a novel method to refine stretching-out finger joint locations after
obtaining rough hand pose estimation. It first detects which fingers are
stretching out, then neighbor pixels of certain joint vote for its new location
based on random forests. The algorithm is tested on two public datasets: MSRA15
and ICVL. After the refinement stage of stretching-out fingers, errors of
predicted HMI finger joint locations are significantly reduced. Mean error of
all fingertips reduces around 5mm (relatively more than 20%). Stretching-out
fingertip locations are even more precise, which in MSRA15 reduces 10.51mm
(relatively 41.4%).
