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林之钊, 黄惠. 从单幅图像生成人物三维动画[J]. 计算机辅助设计与图形学学报, 2022, 34(9): 1341-1350. DOI: 10.3724/SP.J.1089.2022.19166
引用本文: 林之钊, 黄惠. 从单幅图像生成人物三维动画[J]. 计算机辅助设计与图形学学报, 2022, 34(9): 1341-1350. DOI: 10.3724/SP.J.1089.2022.19166
Lin Zhizhao, Huang Hui. 3D Character Animation Generation from a Single Image[J]. Journal of Computer-Aided Design & Computer Graphics, 2022, 34(9): 1341-1350. DOI: 10.3724/SP.J.1089.2022.19166
Citation: Lin Zhizhao, Huang Hui. 3D Character Animation Generation from a Single Image[J]. Journal of Computer-Aided Design & Computer Graphics, 2022, 34(9): 1341-1350. DOI: 10.3724/SP.J.1089.2022.19166

从单幅图像生成人物三维动画

3D Character Animation Generation from a Single Image

  • 摘要: 传统的人物建模和动画绑定方法对人员专业性有较高要求,同时也涉及多种大型商业软件使用.提出一种从单幅图像中生成三维人物动画的方法.首先,借助基于深度学习的隐函数重建方法从图像中获得人物静态三维模型;然后,使用模板参数模型进行形状拟合匹配;最后,配准后参数模型的参数信息正确地迁移到静态模型上,使其可以自由变形以及被动画驱动,并基于该方法构建了应用系统.从模型匹配结果、动画生成结果和人物模型质量等方面对所提方法进行评估,实验合成的图片结果清晰度及人体关键点识别正确率表明,与当前主流的方法相比,所提方法能够获得更加优越的结果.

     

    Abstract: Traditional character modeling and animation rigging methods require a high degree of professionalism and involve the use of a variety of large-scale commercial software.A method to generate 3D character animation from a single image is proposed.First of all,a static 3D model of a person is obtained from the image with the help of an implicit function reconstruction method based on deep learning.Secondly,a template parametric model is used for fitting,and finally the parameter information of the aligned parametric model is correctly transferred to the static model so that it can be freely deformed and driven by animation.In addition,an application system is built upon proposed method with a friendly user interface.Proposed method has been carefully evaluated regarding the quality of model matching,animation generation and character model generation.The experimental results clearly demonstrate the superiority of the proposed technique,compared with mainstream methods.

     

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