Shape from Suggestive Contours Using 3D Priors

S. Wuhrer, Chang Shu
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引用次数: 4

Abstract

This paper introduces an approach to predict the three-dimensional shape of an object belonging to a specific class of shapes shown in an input image. We use suggestive contour, a shape-suggesting image feature developed in computer graphics in the context of non-photorealistic rendering, to reconstruct 3D shapes. We learn a functional mapping from the shape space of suggestive contours to the space of 3D shapes and use this mapping to predict 3D shapes based on a single input image. We demonstrate that the method can be used to predict the shape of deformable objects and to predict the shape of human faces using synthetic experiments and experiments based on artist drawn sketches and photographs.
形状从暗示轮廓使用3D先验
本文介绍了一种预测物体三维形状的方法,该物体属于输入图像中显示的特定形状类。我们使用暗示性轮廓(一种在非真实感渲染的背景下在计算机图形学中发展起来的暗示形状的图像特征)来重建3D形状。我们学习了从暗示轮廓的形状空间到3D形状空间的函数映射,并使用该映射来预测基于单个输入图像的3D形状。我们证明了该方法可以用于预测可变形物体的形状,并通过合成实验和基于艺术家绘制的草图和照片的实验来预测人脸的形状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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