Model-based 3D hand posture estimation from a single 2D image

作者:

Highlights:

摘要

Passive sensing of the 3D geometric posture of the human hand has been studied extensively over the past decade. However, these research efforts have been hampered by the computational complexity caused by inverse kinematics and 3D reconstruction. In this paper, our objective focuses on 3D hand posture estimation based on a single 2D image. We introduce the human hand model with 27 degrees of freedom (DOFs) and analyze some of its constraints to reduce the 27 to 12 DOFs without any significant degradation of performance. A novel algorithm to estimate the 3D hand posture from eight 2D projected feature points is proposed. Experimental results using real images confirm that our algorithm gives good estimates of the 3D hand pose.

论文关键词:3D hand posture estimation,Model-based approach,Gesture recognition

论文评审过程:Received 9 October 2000, Revised 6 October 2001, Accepted 31 October 2001, Available online 13 January 2002.

论文官网地址:https://doi.org/10.1016/S0262-8856(01)00094-4