Stereovision based 3D hand gesture recognition for pervasive computing applications

Hand gesture recognition, being one of the most intuitive means of Human Computer Interface has spawned many applications in the area of pervasive computing devices. This paper presents a solution for hand gesture recognition problem based on 3D stereo imaging techniques employing a low complexity algorithm on a low cost sensor. This method significantly improves upon conventional 2D techniques which are limited in their approach due to various reasons which include but are not limited to occlusion, difficulty in establishing classifiers, segmentation problems using template matching and noise. The innovation here is the use of a hybrid method that combines a simple state machine, skin tone detection and stereo cameras to provide a fast method for detecting simple hand gestures that can be implemented on most low cost System on Chips (SoC). The experimental results from the test setup are promising.