  This paper presents a comprehensive review on regression-based method for
human pose estimation. The problem of human pose estimation has been
intensively studied and enabled many application from entertainment to
training. Traditional methods often rely on color image only which cannot
completely ambiguity of joint 3D position, especially in the complex context.
With the popularity of depth sensors, the precision of 3D estimation has
significant improvement. In this paper, we give a detailed analysis of
state-of-the-art on human pose estimation, including depth image based and
RGB-D based approaches. The experimental results demonstrate their advantages
and limitation for different scenarios.
