Dance-the-music : an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates

In this article, a computational platform is presented, entitled “Dance-the-Music”, that can be used in a dance educational context to explore and learn the basics of dance steps. By introducing a method based on spatiotemporal motion templates, the platform facilitates to train basic step models from sequentially repeated dance figures performed by a dance teacher. Movements are captured with an optical motion capture system. The teachers’ models can be visualized from a first-person perspective to instruct students how to perform the specific dance steps in the correct manner. Moreover, recognition algorithms-based on a template matching method can determine the quality of a student’s performance in real time by means of multimodal monitoring techniques. The results of an evaluation study suggest that the Dance-the-Music is effective in helping dance students to master the basics of dance figures

3D Human Action Recognition Using Spatio-Temporal Motion Templates

Abstract. Our goal is automatic recognition of basic human actions, such as stand, sit and wave hands, to aid in natural communication between a human and a computer. Human actions are inferred from human body joint motions, but such data has high dimensionality and large spatial and temporal variations may occur in executing the same action. We present a learning-based approach for the representation and recognition of 3D human action. Each action is represented by a template consisting of a set of channels with weights. Each channel corresponds to the evolution of one 3D joint coordinate and its weight is learned according to the Neyman-Pearson criterion. We use the learned templates to recognize actions based on χ 2 error measurement. Results of recognizing 22 actions on a large set of motion capture sequences as well as several annotated and automatically tracked sequences show the effectiveness of the proposed algorithm. 1 Introduction and Related Wor