A differential method for computing local shape-from-texture for planar and curved surfaces

Jitendra Malik, R. Rosenholtz
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引用次数: 7

Abstract

We model the texture distortion at a point in any particular direction on the image plane as an affine transformation and derive the relationship between the parameters of the affine transformation and the surface shape and orientation. We use a technique for estimating affine transforms between nearby image patches which is based on solving a system of linear constraints derived from a differential analysis. It is not necessary to explicitly identify texels or make restrictive assumptions about the nature of the image texture like isotropy. We have developed two different algorithms for recovering surface orientation and shape based on the estimated affine transforms in a number of different directions. The first is a sample linear algorithm based on singular value decomposition. The second is based on nonlinear minimization of a least squares error criterion. Experimental results are presented on images of planar and curved surfaces under perspective projection.<>
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平面和曲面局部纹理形状的微分计算方法
我们将图像平面上任意方向上一点的纹理畸变建模为仿射变换,并推导出仿射变换参数与表面形状和方向之间的关系。我们使用一种技术来估计附近图像补丁之间的仿射变换,该技术基于求解微分分析得出的线性约束系统。没有必要明确地识别texel或对图像纹理的性质(如各向同性)做出限制性假设。我们开发了两种不同的算法来恢复表面的方向和形状基于估计的仿射变换在许多不同的方向。首先是基于奇异值分解的样本线性算法。第二种是基于最小二乘误差准则的非线性最小化。给出了透视投影下平面和曲面图像的实验结果。
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