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Photometric Stereo for Micro-scale Shape Reconstruction

机译:光度立体微尺度造型重建

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摘要

This dissertation proposes an approach for 3D micro-scale shape reconstruction using photometric stereo (PS) with surface normal integration (SNI). Based on the proposed approach, a portable cost-effective stationary system is developed to capture 3D shapes in the order of micrometer scale. The PS with SNI technique is adopted to reconstruct 3D microtopology since this technique is highlighted for its capability to reproduce fine surface details at pixel resolution. Furthermore, since the primary hardware components are merely a camera and several typical LEDs, the system based on PS with SNI can be made portable at low cost.;The principal contributions are three folds. First, a PS method based on dichromatic reflectance model (DRM) using color input images is proposed to generalize PS applicable to a wider range of surfaces with non-Lambertian reflectances. The proposed method not only estimates surface orientations from diffuse reflection but also exploits information from specularities owing to the proposed diffuse-specular separation algorithm. Using the proposed PS method, material-dependent features can be simultaneously extracted in addition to surface orientations, which offers much richer information in understanding the 3D scene and poses more potential functionalities, such as specular removal, intrinsic image decomposition, digital relighting, material-based segmentation, material transfer and material classification.;The second contribution is the development of an SNI method dealing with perspective distortion. The proposed SNI is performed on the image plane instead of on the target surface as did by orthographic SNI owing to the newly derived representation of surface normals. The motivation behind the representation is from the observation that spatially uniform image points are simpler for integration than the non-uniform distribution of surface points under perspective projection. The new representation is then manipulated to the so-called log gradient space in analogy to the gradient space in orthographic SNI. With this analogy, the proposed method can inherit most past algorithms developed for orthographic SNI. By applying the proposed SNI, perspective distortion can be efficiently tackled with for smooth surfaces. In addition, the method is PS-independent, which can keep the image irradiance equation in a simple form during PS.;The third contribution is the design and calibration of a 3D micro-scale shape reconstruction system using the derived PS and SNI methods. This system is originally designed for on-site measurement of pavement microtexture, while its applicability can be generalized to a wider range of surfaces. Optimal illumination was investigated in theory and through numerical simulations. Five different calibrations regarding various aspects of the system were either newly proposed or modified from existing methods. The performances of these calibrations were individually evaluated. Efficacy of the developed system was finally demonstrated through comprehensive comparative studies with existing systems. Its capability for on-site measurement was also confirmed.
机译:本文提出了一种利用光度立体(PS)和表面法向积分(SNI)的3D微尺度形状重构方法。基于提出的方法,开发了一种便携式经济高效的固定系统,以捕获微米级的3D形状。采用具有SNI技术的PS来重建3D微拓扑,因为该技术因其能够以像素分辨率重现精细的表面细节而得到强调。此外,由于主要的硬件组件只是一个摄像头和几个典型的LED,因此基于PS和SNI的系统可以以低成本实现便携式。主要贡献是三倍。首先,提出了一种基于彩色输入图像的基于双色反射模型(DRM)的PS方法,以推广适用于具有非朗伯反射率的较大范围表面的PS。所提出的方法不仅根据漫反射来估计表面方向,而且由于所提出的漫反射镜分离算法而利用了来自镜面反射的信息。使用提出的PS方法,除了表面方向外,还可以同时提取与材料相关的特征,这为理解3D场景提供了更丰富的信息,并带来了更多潜在的功能,例如镜面去除,固有图像分解,数字重新照明, ;第二个贡献是开发了一种处理透视变形的SNI方法。由于重新获得的表面法线表示,建议的SNI在图像平面上执行,而不是像正射SNI在目标表面上执行。该表示背后的动机来自观察到,与透视投影下的表面点的不均匀分布相比,空间上均匀的图像点更易于集成。然后,类似于正交SNI中的梯度空间,将新的表示形式处理到所谓的对数梯度空间。以此类推,所提出的方法可以继承过去为正交SNI开发的大多数算法。通过应用建议的SNI,可以有效解决透视失真的问题,从而获得平滑的表面。此外,该方法与PS无关,可以使PS期间的图像辐照度方程保持简单形式。第三点是使用派生的PS和SNI方法设计和校准3D微型形状重建系统。该系统最初设计用于路面微纹理的现场测量,而其适用性可以推广到更广泛的表面。在理论上和通过数值模拟研究了最佳照明。关于系统各个方面的五种不同的校准是新提出的,或者是从现有方法中修改的。分别评估了这些校准的性能。最终通过与现有系统的全面比较研究证明了已开发系统的功效。还证实了其现场测量的能力。

著录项

  • 作者

    Li, Boren.;

  • 作者单位

    Virginia Polytechnic Institute and State University.;

  • 授予单位 Virginia Polytechnic Institute and State University.;
  • 学科 Information technology.;Artificial intelligence.;Robotics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 162 p.
  • 总页数 162
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:46:45

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