Gesture-based editing system for graphic primitives and alphanumeric characters
This paper presents a system that edits graphic primitives and alphanumeric characters using hand gestures in natural environments. Gesture is one of the most natural means of enhancing human-computer interaction (HCI) techniques to the level of human communication. This research aims to recognize one-stroke pictorial gestures from visual images, and to develop a graphic/text editing system running in real time. The tasks are performed through three steps: moving-hand tracking and trajectory generation, key-gesture segmentation, and gesture recognition by analyzing dynamic features. A gesture vocabulary consists of 48 gestures of three types: (1) six editing commands; (2) six graphic primitives; and (3) alphanumeric characters26 alphabetic and 10 numerical. A meaningful gesture part is segmented by a spotter using the phase-based velocity constraints. Some dynamic features are obtained from spatio-temporal trajectories and quantized by the K-means algorithm. The quantized vectors were trained and tested using hidden Markov models (HMMs). Experimental results show about 88.5% correct recognition rate, and also the practical potential for applying these techniques to several areas such as the remote control of robots or of electronic household appliances, or object manipulation in VR systems.
gesture recognition visual gesture images hand tracking spotting vector quantization