ABSTRACT
3D Hand Pose Estimations an important research content in the field of human-computer interaction, virtual reality, augmented reality and other gesture interaction. In this paper, 3D hand pose surface estimation based on personalized hand features is proposed and applied to guqin performance. We constructed the database of basic finger-pointing for guqin performance,and based on the Mask R-CNN and FPN network structure, a new MMFPN structure is proposed, which can not only realize the three-dimensional surface estimation of basic finger-pointing, but also effectively solve the problem of self-occlusion.
- Rui Li, ZhengyuLiu,Jianrong Tan. A survey on 3D hand pose estimation: Cameras, methods, and datasets. Pattern Reconition.2019,93:251-272Google Scholar
- L.Dipietro, A.M.Sabatini, P.Dario, A survey of glove-based systems and theirapplications, IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 2018,38 (4):461-482.Google ScholarDigital Library
- J.M.Rehg, T.Kanade, Visual tracking of high DOF articulated structures: anapplication to human hand tracking, Eur. Conf. Comput. Vis. 1994,801: 35-46.Google Scholar
- AmmarAhmad,CyrilleMiniot,AlberDipanda. Hand pose estimation and tracking in real and virtual interaction:Areview.Image and Vision Computing .2019,89:35-49Google Scholar
- A.Erol, G. Bebis, M. , Vision-based hand poseestimation: a review, Comput. Vis. Image Underst. 2017,108 (1-2): 52-73.Google ScholarDigital Library
- Yiming He, Wei Hu, GraphPoseGAN: 3D Hand Pose Estimation from aMonocular RGB Image via Adversarial Learning onGraphs.Computer Vision and Pattern Recognition .2019Google Scholar
- SHARP T, KESKIN C, ROBERTSON D, Accurate,robust, and flexible real-time hand tracking[C]//Proceedingsof the 33th Annual ACM Conference on Human Factors inComputing Systems. Seoul, Republic of Korea: ACM, 2015:3633-3642.Google Scholar
- L.Ge, H.Liang ,J.Yuan , D.Thalmann , 3D convolutional neural networks for efficient and robust hand pose estimation from single depth images, in: IEEE Computer Vision and Pattern Recognition, 2017:5679–5688 .Google Scholar
- Kuang Y.Q.,Cheng H.,Cui F.,Semi-supervised hand pose estimation algorithm based on multi-view projection, Journal of University of Electronic Science and Technology of China.2019,48(5):747-753Google Scholar
- LiuhaoGe, Zhou Ren , 3D Hand Shape and Pose Estimation from a Single RGB Image.in CVPR2019.Google Scholar
- Xiong Zhang, Qiang Li, End-to-end Hand Mesh Recovery from a Monocular RGB Image. Computer Vision and Pattern Recognition.2019Google Scholar
- L. Ge, H.Liang, Real-time 3D hand pose estimation with 3D convolutional neural networks, IEEE Trans. Pattern Anal. Mach. Intell. 2019,41 (4) :956–970.Google ScholarDigital Library
- Varol G, Ceylan D, Bodynet:Volumetric inference of 3D human body shapes[C]//Proceedings of the European Conference on Computer Vision, 2018:20-36.Google Scholar
- Pavllo D, Feichtenhofer C, 3D human pose estimation in video with temporal convolutions andsemi-supervised training[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019:7753-7762.Google Scholar
- Zeng Z. C.,Li G. Q.,Posture and shape reconstruction of 3d mannequin. Journal of Computer Aided Design and Graphics.2019,32(9):1485-1493。Google Scholar
- Franziska Mueller, Micah Davis, Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera. ACM Trans. Graph.38, 4, Article 49 (July 2019), 13 pages. https://doi.org/10.1145/3306346.3322958]Google Scholar
- Jameel Malik, Ahmed Elhayek, DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning fromSynthetic Depth. Computer Vision and Pattern Recognition.2018]Google Scholar
- L.Ge, H.Liang,J.Yuan ,D.Thalmann , 3D convolutional neural networks for efficient and robust hand pose estimation from single depth images, in: IEEE Computer Vision and Pattern Recognition, 2017:5679–5688 .Google Scholar
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