Human Action Recognition Using Laban Movement Analysis and Dynamic Time Warping

Abstract

Bilateral interaction between humans and robots is one of the areas that has attracted much attention in recent years. Automation of human behavior recognition is one of the main steps in achieving this goal. In this regard, in this paper we have designed a process for automatic identification of human gestures. The process consists of two main parts. In the first part, by using the Laban Movement Analysis method, we define a robust descriptor, and in the second part, we determine the robustness of the descriptor using the Dynamic time Warping algorithm. The method proposed in this paper has been tested on four public data-sets namely MSR Action 3D, Florence 3D actions, UTKinect-Action3D and SYSU 3D HUMAN-OBJECT INTERACTION data-sets. Given the results obtained from previous work, the efficiency of the proposed method can be more accurately understood. The results obtained confirm the effectiveness and the performance of our model which outperforms results presented in similar works on action recognition.