Robust 3D Hand Detection for Gestures Recognition

The aim of this paper is to present a fast, robust and adaptive method for real-time 3D hand detection. Unlike traditional 2D approaches which are based on skin or features detection, the proposed method relies on depth information obtained from a stereoscopic video system. As a result, it provides the 3D position of both hands. It also deals with changes of lighting and it is capable of detecting the hands from long distances. The experimental results showed that our method can be successfully integrated in various and complex vision-based systems requiring real-time recognition of hands gestures in 3D environments.