  Not all the human body parts have the same~degree of freedom~(DOF) due to the
physiological structure. For example, the limbs may move more flexibly and
freely than the torso does. Most of the existing 3D pose estimation methods,
despite the very promising results achieved, treat the body joints equally and
consequently often lead to larger reconstruction errors on the limbs. In this
paper, we propose a progressive approach that explicitly accounts for the
distinct DOFs among the body parts. We model parts with higher DOFs like the
elbows, as dependent components of the corresponding parts with lower DOFs like
the torso, of which the 3D locations can be more reliably estimated. Meanwhile,
the high-DOF parts may, in turn, impose a constraint on where the low-DOF ones
lie. As a result, parts with different DOFs supervise one another, yielding
physically constrained and plausible pose-estimation results. To further
facilitate the prediction of the high-DOF parts, we introduce a pose-attribute
estimation, where the relative location of a limb joint with respect to the
torso, which has the least DOF of a human body, is explicitly estimated and
further fed to the joint-estimation module. The proposed approach achieves very
promising results, outperforming the state of the art on several benchmarks.
