Practical Hand Skeleton Estimation Method Based on Monocular Camera

Abstract

In this paper, we propose a practical hand skeleton reconstruction method using a monocular camera. The proposed method is a fundamental technology that can be applicable to future products such as wearable or mobile devices and smart TVs requiring natural hand interactions. To heighten its practicability, we designed our own hand parameters composed of global hand and local finger configurations. Based on the parameter states, a kinematic hand and its contour can be reconstructed. By adopting palm detection and tracking, global parameters can be easily estimated, which can reduce the search space required for whole parameter estimations. We can then fine-tune the coarse estimated parameters through the use of a Gauss-Newton optimization stage. Experimental results indicate that our method provides a sufficient level of accuracy to be utilized in gesture-interactive applications. The proposed method is light in terms of algorithm complexity and can be applied in real time.