Real-time 3D hand pose estimation with 3D convolutional neural networks

• المؤلفون الرئيسيون: Ge, Liuhao, Liang, Hui, Yuan, Junsong, Thalmann, Daniel
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2019
• الموضوعات: 3D Convolutional Neural Networks; DRNTU::Engineering::Electrical and electronic engineering; 3D Hand Pose Estimation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/106412; http://hdl.handle.net/10220/47912; http://dx.doi.org/10.1109/TPAMI.2018.2827052
• المؤسسة: Nanyang Technological University

In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose estimation due to the lack of 3D spatial information. Our propos...