Pose evaluation for dance learning application using joint position and angular similarity

In this paper, we propose a dance pose evaluation method for a dance learning application using a smartphone. In the past, methods for classifying and comparing dance gestures through 3-D joint information obtained through a 3-D camera have been proposed, but there is a problem in using them for accurate dance pose evaluation. That is, these methods simply compare the similarity between the dance gestures without evaluation of the exact dance pose. To solve this problem, we propose a new method that can be operated on a smartphone for exact dance pose evaluation that simultaneously performs an affine transformation and an evaluation method to compare the joint position and joint angle information. In addition, we prove that the proposed method is suitable for dance learning applications through comparative experiments on a smartphone with real-world datasets.