Nonlinearities and Noise Reduction in 3-Source Photometric Stereo

1-D Leap-Frog (L. Noakes, J. Math. Australian Soc. A, Vol. 64, pp. 37–50, 1999) is an iterative scheme for solving a class of nonquadratic optimization problems. In this paper a 2-D version of Leap-Frog is applied to a non optimization problem in computer vision, namely the recovery (so far as possible) of an unknown surface from 3 noisy camera images. This contrasts with previous work on photometric stereo, in which noise is added to the gradient of the height function rather than camera images. Given a suitable initial guess, 2-D Leap-Frog is proved to converge to the maximum-likelihood estimate for the vision problem. Performance is illustrated by examples.     

基于光度立体法的汽车零件字符识别预处理研究

为了提高工业自动化对汽车零件上字符的自动识别效率,论文针对汽车零件上字符颜色一般与背景色相近,两者对比度非常低的问题,提出了基于光度立体法的汽车零件字符预处理方法.首先从四个不同方向对物体进行照明收集图片,利用四张采集的图片计算物体三维表面的局部梯度,然后继续计算物体表面的旋度、散度、平均曲率和高斯曲率,最终得到对比度...     

Design Issues for a Colour Photometric Stereo System

This paper presents the detailed performance analysis for a colour photometric stereo system proposed recently. The system recovers surface colour and surface normal for each surface patch separately, in the presence of highlights and shadows. The error analysis presented concerns every step of the algorithm, and it is based on the assumptions that errors may arise due to Gaussian image noise and errors in the accuracy with which the geometry of the illuminating set-up is known. The analysis is confirmed by experiments. The implications of this sensitivity analysis to the design of such a rig and the choice of threshold values for the algorithm are also discussed and recommendations to a designer are given.     

近光源光度立体三维重建误差分析

一般假设的平行光光源,即远光源模型,受安装空间的约束在现实世界中很难实现。针对这一问题,提出了近光源模型解决近光源大尺寸物体的三维重建。近光源模型是一种新型的光源位置假设,需要标定光源位置,计算目标物体每个点上的光线方向,这样即使当物体尺寸较大或距离光源较近时,近光源模型也是对光源较优的一种假设。通过分析上述两种光源模型对噪声、光源到目标物体距离等因素的敏感度,比较发现当光源距离物体较近或物体尺寸较大的情况下,近光源模型的重建结果优于远光源的重建结果。     

一种基于近似点光源模型的光度立体视觉系统 标定方法

文章研究了一种由近似点光源组成的光度立体视觉系统的标定方法。由于光源自身的非均匀发光特性,传统的平行光和点光源模型不再适用,为实现精确的三维法向重建,必须对光源及光照场进行精确的标定。论文首先根据光源自身的发光特性建立其辐射度模型,进而提出了一种两步标定策略,对光源位置参数及主光轴参数进行标定。以相机作为参照系,提出了一种多球标定方法,用于计算各个光源的位置参数,该方法利用相机观察到的多个球面高光点图像坐标,结合球体轮廓线及球体半径实现了光源位置的精确计算。为实现光源主光轴参数的估算,提出了一种基于参考平面的标定方法,通过分析近似点光源照射下的平面亮度分布,结合等亮度线拟合策略实现了光源主光轴方向参数的计算。基于系统标定参数以及光源的发光模型,就可以对每个场景点的入射光条件进行精确建模,从而实现精确的法向计算。在实验部分,分别对标准几何物体和自由曲面物体进行三维重建实验,并与传统的平行光及点光源模型进行了对比。结果显示,所提出的标定方法能够在非均匀光照条件下获得精确的三维法向重建结果。     

基于光度立体和图像显著性的皮革缺陷检测

为了提高皮革缺陷检测效率，提出一种基于光度立体视觉和图像显著性的皮革缺陷检测算法。搭建光度立体视觉平台，完成不同角度的皮革样本采集，利用光度立体视觉技术计算皮革样本的合成图和表面法向量图；对表面法向量图进行曲率滤波操作，用近似表面粗糙度特征自适应选择合成图或滤波图；利用显著性目标检测算法完成皮革缺陷检测与定位。实验结果表明，与现有皮革缺陷检测方法相比，该算法能很好地检测不同材质皮革的多种缺陷，且准确率高，速度快。     

Generalization of the Lambertian model and implications for machine vision

Lambert's model for diffuse reflection is extensively used in computational vision. It is used explicitly by methods such as shape from shading and photometric stereo, and implicitly by methods such as binocular stereo and motion detection. For several real-world objects, the Lambertian model can prove to be a very inaccurate approximation to the diffuse component. While the brightness of a Lambertian surface is independent of viewing direction, the brightness of a rough diffuse surface increases as the viewer approaches the source direction. A comprehensive model is developed that predicts reflectance from rough diffuse surfaces. The model accounts for complex geometric and radiometric phenomena such as masking, shadowing, and interreflections between points on the surface. Experiments have been conducted on real samples, such as, plaster, clay, sand, and cloth. All these surfaces demonstrate significant deviation from Lambertian behavior. The reflectance measurements obtained are in strong agreement with the reflectance predicted by the proposed model. The paper is concluded with a discussion on the implications of these results for machine vision.     

Lighting Estimation of a Convex Lambertian Object Using Redundant Spherical Harmonic Frames

An explicit lighting estimation from a single image of Lambertian objects is influenced by two factors: data incompletion and noise contamination. Measurement of lighting consistency purely using the orthogonal spherical harmonic basis cannot achieve an accurate estimation. We present a novel signal-processing framework to represent the lighting field. We construct a redundant spherical harmonic frame with geometric symmetry on the sphere S ². Spherical harmonic frames are defined over the generating rotation matrices about symmetry axes of finite symmetry subgroups of SO(3), and the generating functions are spherical harmonic basis functions. Compared with the orthogonal spherical harmonic basis, the redundant spherical harmonic frames not only describe the multidirectional lighting distribution intuitively, but also resist the noise theoretically. Subsequently, we analyze the relationship of the irradiance to the incoming radiance in terms of spherical harmonic frames, and reconstruct the lighting function filtered by the Lambertian BRDF (bidirectional reflectance distribution function). The experiments show that the frame coefficients of spherical harmonic frames can better characterize the complex lighting environments finely and robustly.     

Recognition of shiny dielectric objects by analysing the polarization of reflected light

The degree of polarization of light reflected from a transparent or translucent object depends only upon the angle of incidence, refractive index and absorption coefficient of the material. It is therefore possible to determine the orientation of the surface normal from the direction of the plane of polarization. The feasibility of this is demonstrated both theoretically and practically by calculating and measuring the reflectance map of a sphere when viewed through a plane polarizing filter. Ambiguities in the mapping from radiance to orientation are removed by orienting the filter at three angles. The orientation of our objects is determined to within an uncertainty of less than seven degrees.     

Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction

We present a method—termed Helmholtz stereopsis—for reconstructing the geometry of objects from a collection of images. Unlike existing methods for surface reconstruction (e.g., stereo vision, structure from motion, photometric stereopsis), Helmholtz stereopsis makes no assumptions about the nature of the bidirectional reflectance distribution functions (BRDFs) of objects. This new method of multinocular stereopsis exploits Helmholtz reciprocity by choosing pairs of light source and camera positions that guarantee that the ratio of the emitted radiance to the incident irradiance is the same for corresponding points in the two images. The method provides direct estimates of both depth and surface normals, and consequently weds the advantages of both conventional stereopsis and photometric stereopsis. Results from our implementation lend empirical support to our technique.     

基于立体视觉的机械手未知平面内曲线跟踪

为了提高机械手应用的灵活性,增强机械手对动态环境的适应能力,降低机械手对工件位置的依赖性,采用立体视觉技术对未知平面的法线方向进行估计,根据工程应用中对末端执行器的速度以及位姿的实际要求,采用PID控制策略控制机械手末端执行器与工件之间的相对位姿.进行了仿真实验以验证所提方法的有效性,结果表明:该方法能够实现末端执行器和工件之间相对位姿的动态控制.     

一种鲁棒的基于光度立体视觉的表面重建方法

提出一种基于先进的凸优化技术的光度立体视觉重建框架. 首先通过鲁棒的主成分分析(Robust principle component analysis, RPCA)祛除图像噪声, 得到低秩矩阵和物体表面向量场, 然后再通过表面重建算法从向量场来恢复物体形状. 相对于先前的一些使用最小二乘或者一些启发式鲁棒技术的方法, 该方法使用了所有可用的信息, 可以同时修复数据中的丢失和噪声数据, 显示出了较高的计算效率以及对于大的稀疏噪声的鲁棒性. 实验结果表明, 本文提出的框架大大提高了在噪声存在情况下物体表面的重建精度.     

Recovering Shape by Shading and Stereo Under Lambertian Shading Model

A method that integrates shape from shading and stereo is reported for Lambertian objects. A rectification is proposed to convert any lighting direction from oblique to orthographic. A sparse stereo method is reported that directly uses depth information and has no foreshortening problem. The method completely solves three difficult problems in stereo, namely, recovering depth at occlusion; matching at places with similar shading and matching at smooth silhouettes. The method has been tested on both synthetic and real images. It shows superior performance compared with two recent stereo algorithms. It is also a method based on the physics of image formation. The work described in this article was fully supported by a grant from CityU (7002128).     

保持自然度的非均匀光照图像增强的Retinex算法

常规的非均匀照明图像增强方法在增强低光照区域细节时,容易对图像过度增强而导致结果失真.本文从一种新的角度提出了Retinex模型的一种扩展形式,并用于非均匀照明图像的增强.该算法将中心环绕Retinex模型输出作为感知反射率,将图像分解为感知光照图像和感知反射率图像,通过调整感知光照图像,再重新组合感知光照和感知反射率...     

颠簸环境下的快速障碍物检测算法

障碍物检测是智能车辆研究中的一个重要内容.用射影几何的方法给出了用重投影变换进行障碍物检测的一般原理,并引入摄像机的内、外参数和姿态参数,建立了重投影变换的参数化模型.为了满足颠簸环境的要求,提出了一种新的基于立体视觉视差分析的障碍物检测算法.实验结果表明,算法具有计算量小和可靠性高的特点.     

Stereo Image Analysis of Non-Lambertian Surfaces

Stereo image analysis is based on establishing correspondences between a pair of images by determining similarity measures for potentially corresponding image parts. Such similarity criteria are only strictly valid for surfaces with Lambertian (diffuse) reflectance characteristics. Specular reflections are viewpoint dependent and may thus cause large intensity differences at corresponding image points. In the presence of specular reflections, traditional stereo approaches are often unable to establish correspondences at all, or the inferred disparity values tend to be inaccurate, or the established correspondences do not belong to the same physical surface point. The stereo image analysis framework for non-Lambertian surfaces presented in this contribution combines geometric cues with photometric and polarimetric information into an iterative scheme that allows to establish stereo correspondences in accordance with the specular reflectance behaviour and at the same time to determine the surface gradient field based on the known photometric and polarimetric reflectance properties. The described approach yields a dense 3D reconstruction of the surface which is consistent with all observed geometric and photopolarimetric data. Initially, a sparse 3D point cloud of the surface is computed by traditional blockmatching stereo. Subsequently, a dense 3D profile of the surface is determined in the coordinate system of camera 1 based on the shape from photopolarimetric reflectance and depth technique. A synthetic image of the surface is rendered in the coordinate system of camera 2 using the illumination direction and reflectance properties of the surface material. Point correspondences between the rendered image and the observed image of camera 2 are established with the blockmatching technique. This procedure yields an increased number of 3D points of higher accuracy, compared to the initial 3D point cloud. The improved 3D point cloud is used to compute a refined dense 3D surface profile. These steps are iterated until convergence of the 3D reconstruction. An experimental evaluation of our method is provided for areas of several square centimetres of forged and cast iron objects with rough surfaces displaying both diffuse and significant specular reflectance components, where traditional stereo image analysis largely fails. A comparison to independently measured ground truth data reveals that the root-mean-square error of the 3D reconstruction results is typically of the order 30–100 μm at a lateral pixel resolution of 86 μm. For two example surfaces, the number of stereo correspondences established by the specular stereo algorithm is several orders of magnitude higher than the initial number of 3D points. For one example surface, the number of stereo correspondences decreases by a factor of about two, but the 3D point cloud obtained with the specular stereo method is less noisy, contains a negligible number of outliers, and shows significantly more surface detail than the initial 3D point cloud. For poorly known reflectance parameters we observe a graceful degradation of the accuracy of 3D reconstruction.     

利用光度立体法生成真实物体的三维模型

在计算机三维动画制作中，要制作一个具体的真实物体的三维模型，是一项复杂而困难的事情。本文根据由阴影恢复形状的视觉理论，利用光度立体视觉技术，给出了由３幅光移图象计算物体表面方向和深度信息，并利用贝塞尔曲线拟合获得物体表面的结构模型的方法。     

一种光照度不一致鲁棒立体匹配算法

为了提高光照度不一致立体图像对的匹配率,提出一种基于对数颜色空间下改进极线距离变换的立体匹配算法.在对数颜色空间下,首先根据初始视差图计算立体图像对的灰度比;然后,采用与灰度比成比例的灰度误差系数,分别对左右图像进行极线距离变换;最后利用置信度传播算法计算视差图.理论上,本文算法的匹配结果不会受光源位置、光源谱分布、光照强度以及摄像机参数设置等光照度不一致因素的影响.实验表明:本文算法的匹配率相对于原始极线距离变换算法最多可提高60%;而应用于弱纹理图像对时,相对于当前先进的自适应归一化算法,匹配率最多可提高78%.     

Stereo with Oblique Cameras

Mosaics acquired by pushbroom cameras, stereo panoramas, omnivergent mosaics, and spherical mosaics can be viewed as images taken by non-central cameras, i.e. cameras that project along rays that do not all intersect at one point. It has been shown that in order to reduce the correspondence search in mosaics to a one-parametric search along curves, the rays of the non-central cameras have to lie in double ruled epipolar surfaces. In this work, we introduce the oblique stereo geometry, which has non-intersecting double ruled epipolar surfaces. We analyze the configurations of mutually oblique rays that see every point in space. These configurations, called oblique cameras, are the most non-central cameras among all cameras. We formulate the assumption under which two oblique cameras posses oblique stereo geometry and show that the epipolar surfaces are non-intersecting double ruled hyperboloids and two lines. We show that oblique cameras, and the correspondingoblique stereo geometry, exist and give an example of a physically realizable oblique stereo geometry. We introduce linear oblique cameras as those which can be generated by a linear mapping from points in space to camera rays and characterize those collineations which generate them. We show that all linear oblique cameras are obtained by a collineation from one example of an oblique camera. Finally, we relate oblique cameras to spreads known from incidence geometries.     

一种室外非理想光照条件下的立体匹配算法

针对室外非理想光照条件和图像低纹理、低对比度造成立体匹配效果较差的问题,提出一种HSL(色相-饱和度-亮度)颜色空间下基于边缘图分割的立体匹配算法.区别于传统的RGB颜色空间下基于像素强度的度量方式,该算法采用一种HSL颜色空间下的像素非相似性度量公式来获得匹配代价,然后基于左右输入图像的边缘检测结果进行图像区域分割和立体匹配.在实验中采用一系列不同光照条件的图片集和具有明显低纹理区域的图片集,对本文算法与现有算法进行对比验证.实验结果证明,该算法能够得到比较理想的视差图,对非理想的光照条件和低纹理图像具有很好的鲁棒性,并且基本达到实时性要求.