Semantic recognition of human gestures based on spatial and temporal reasoning

Gesture semantic recognition is a vital process of motion recognition. An accurate and stable recognition method helps to identify semantic meaning of a continuous motion. In this work, the semantic meaning is represented by a sequence of motion primitives. This work proposes a method based on spatial and temporal reasoning. Both spatial and temporal rules of motion primitives are used to estimate the current state of motion. The motion primitives adopted in this work are transport empty (TE), transport loaded (TL), grasp (G), and release (RL) from Gilbreth's therbligs. The results show that the average recognition rate is 94.44% out of three different tasks.