User pose estimation based on multiple depth sensors
Seongmin Baek, Myung-Gyu Kim · 2017
Despite the diverse application of motion capture technology, it is challenging to capture people's motions unless they are wearing relevant equipment. This paper proposes a method of estimating the joint positions based on depth data as well as optimal joint selection in restoring the pose with multiple Kinect sensors. The proposed method enhances the accuracy of pose restoration, enables real-time capture of dynamic motions such as Taekwondo and applies to training programs for the general public.