3-D建模从概念草图的人类角色与最小的用户交互

A. Johnston, G. Carneiro, Ren Ding, L. Velho
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引用次数: 3

摘要

我们提出了一种新的方法,通过最小的用户交互,从人类角色的二维概念草图为计算机图形应用程序创建三维模型。这种方法将有助于参与视频游戏和电影开发过程的非专业用户快速生产高质量的3d模型。该工作流程从单个视点包含人物草图的图像开始,其中运行二维身体姿势检测器来推断人物骨骼关节的位置。然后,从上面检测到的2-D身体姿势中估计3-D身体姿势和相机运动,我们采用最近提出的与真人一起工作的方法,并使其适应于人类角色的概念草图。我们的方法的最后一步包括一个基于采样重要性重采样方法的优化过程,该方法将估计的三维身体姿势和相机运动作为输入,并构建身体形状的三维网格,然后将其与概念草图图像匹配。我们的主要贡献是:1)从二维身体姿势估计方法的新颖的三维适应工作与人类的草图是非标准的身体部位比例和约束相机运动;2)一种新的优化(利用人体形状的底层低维线性模型来估计三维人体网格),以人体形状的三维网格与概念草图之间的匹配质量为指导。我们展示了基于从二维概念草图中推断出的七个三维模型的定性结果,以及定量结果,其中我们采用七个不同的三维网格来生成概念草图,并使用我们的方法从这些草图中推断出三维模型,这使我们能够测量原始模型和估计的三维模型之间的平均欧几里得距离。定性和定量结果表明,该模型具有从概念草图快速生成三维模型的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3-D Modeling from Concept Sketches of Human Characters with Minimal User Interaction
We propose a new methodology for creating 3-D models for computer graphics applications from 2-D concept sketches of human characters using minimal user interaction. This methodology will facilitate the fast production of high quality 3-D models by non-expert users involved in the development process of video games and movies. The workflow starts with an image containing the sketch of the human character from a single viewpoint, in which a 2-D body pose detector is run to infer the positions of the skeleton joints of the character. Then the 3-D body pose and camera motion are estimated from the 2-D body pose detected from above, where we take a recently proposed methodology that works with real humans and adapt it to work with concept sketches of human characters. The final step of our methodology consists of an optimization process based on a sampling importance re-sampling method that takes as input the estimated 3-D body pose and camera motion and builds a 3-D mesh of the body shape, which is then matched to the concept sketch image. Our main contributions are: 1) a novel adaptation of the 3-D from 2-D body pose estimation methods to work with sketches of humans that have non-standard body part proportions and constrained camera motion; and 2) a new optimization (that estimates a 3-D body mesh using an underlying low-dimensional linear model of human shape) guided by the quality of the matching between the 3-D mesh of the body shape and the concept sketch. We show qualitative results based on seven 3-D models inferred from 2-D concept sketches, and also quantitative results, where we take seven different 3-D meshes to generate concept sketches, and use our method to infer the 3-D model from these sketches, which allows us to measure the average Euclidean distance between the original and estimated 3-D models. Both qualitative and quantitative results show that our model has potential in the fast production of 3-D models from concept sketches.
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