Depth extraction of three-dimensional objects in space by the computational integral imaging reconstruction technique

A novel approach to extract the depth data of 3D objects in space by using the computational integral imaging reconstruction (CIIR) technique is proposed. With elemental images of 3D objects captured by the CCD camera through a pinhole array, depth-dependent object images can be reconstructed on the output plane by the CIIR technique. Only the images reconstructed on the output planes where 3D objects were located are clearly focused; so the depth data of 3D objects in space can be extracted by discriminating these focused output images from the others by using an image separation technique. A feasibility test of the proposed CIIR-based depth extraction method is carried out, and its results are discussed as well.     

Three dimension reconstruction through measure-based image selection

Three dimension (3D) reconstruction is one of the research focus of computer vision and widely applied in various fields. The main steps of 3D reconstruction include image acquisition, feature point extraction and matching, camera calibration and production of dense 3D scene models. Generally, not all the input images are useful for camera calibration because some images contain similar and redundant visual information. These images can even reduce the calibration accuracy. In this paper, we propose an effective image selection method to improve the accuracy of camera calibration. Then a new 3D reconstruction algorithm is proposed by adding the image selection step to 3D reconstruction. The image selection method uses structure-from-motion algorithm to estimate the position and attitude of each camera, first. Then the contributed value to 3D reconstruction of each image is calculated. Finally, images are selected according to the contributed value of each image and their effects on the contributed values of other images. Experimental results show that our image selection algorithm can improve the accuracy of camera calibration and the 3D reconstruction algorithm proposed in this paper can get better dense 3D models than the normal algorithm without image selection.     

多通道图像色彩重建的神经网络算法

为了解决目前多光谱成像设备输出的应用问题,将神经网络算法应用于多通道图像色彩重建。CCD相机加LED光源组成多光谱成像系统,研究其输出的多通道图像中色彩信息的高效转换方法,建立了D50光源下的神经网络转换模型,利用BP神经网络和GRNN对多光谱成像系统进行色彩重建实验。研究结果表明：采用搭建的模型可以得到较高的色度重建精度,更换目标样本色彩重建性能保持稳定。     

High-accuracy three-dimensional shape acquisition of a large-scale object from multiple uncalibrated camera views

Acquiring a high-accuracy three-dimensional (3D) shape of a large-scale object from multiple uncalibrated camera views remains a big challenge, since a considerable number of images is required to cover the entire surface; the use of multiple images could, however, result in accumulative errors from each processed image. Here error propagation rules in the 3D reconstruction process have been deduced on the basis of the traditional dual-view reconstruction method. We propose a method that can control the accumulative errors by reducing the times of coordinate transformation with common-view-based dual-view reconstruction. This method involves constructing an image network composed of many image groups, each of which contains a common view. A baseline threshold method is introduced to construct a high-quality image network, and the sums or reprojection residual of all the common points is proposed to assess the validity of the solutions of the orientation. Experiments carried out with both synthetic and real images demonstrate that the proposed method can handle the accumulative error problem with robust and highly accurate results.     

A 3D Measurement Method Based on Coded Image

The binocular stereo vision system is often used to reconstruct 3D point clouds of an object. However, it is challenging to find effective matching points in two object images with similar color or less texture. This will lead to mismatching by using the stereo matching algorithm to calculate the disparity map. In this context, the object can’t be reconstructed precisely. As a countermeasure, this study proposes to combine the Gray code fringe projection with the binocular camera as well as to generate denser point clouds by projecting an active light source to increase the texture of the object, which greatly reduces the reconstruction error caused by the lack of texture. Due to the limitation of the camera viewing angle, a one-perspective binocular camera can only reconstruct the 2.5D model of an object. To obtain the 3D model of an object, point clouds obtained from multiple-view images are processed by coarse registration using the coarse SAC-IA algorithm and fine registration using the ICP algorithm, which is followed by voxel filtering fusion of the point cloud. To improve the reconstruction quality, a polarizer is mounted in front of the cameras to filter out the redundant reflected light. Eventually, the 3D model and the dimension of a vase are obtained after calibration.     

Stereo calibration of binocular ultra-wide angle long-wave infrared camera based on an equivalent small field of view camera

ABSTRACT

In this paper, a stereo calibration method for binocular ultra-wide angle long-wave infrared camera is proposed on the basis of an equivalent small field of view camera. Extrinsic parameters are calibrated through the corrected images from the left and right cameras. They can be viewed as images taken by a small field of view camera. The calibration procedure consists of three steps: monocular calibration, distortion correction and extrinsic parameters calibration. In order to evaluate the accuracy of the method, stereo vision of the camera is modelled and a 3D reconstruction approach is presented. A series of experiments, including intrinsic parameters, extrinsic parameters and 3D reconstruction, are conducted to validate the proposed method. The results show that the baseline length error decreases to 0.67%, and the relative error for the 3D reconstruction of corners is smaller than 8.11%. In contrast to the common stereo calibration method, it improves calibration accuracy.     

AHSPP Annual Conference

Abstract

A calibration and three-dimensional (3D) reconstruction method is presented based on images reflected from planar mirrors and acquired with one camera. The geometric model of the camera–mirror set and a method of calibrating it are described. The calibration technique computes the model parameters using linear equations, and it is proved that the calibration is possible with the knowledge of only six 3D points. The reconstruction method is based on a volumetric representation. The 3D reconstruction is based on a space carving algorithm and the calibration method described in the paper. The results of the calibration and reconstruction method show the efficiency of both techniques. This set-up enables a simple and inexpensive multi-ocular system to be built to recover the 3D structure of volumes.     

3D reconstruction of concave surfaces using polarisation imaging

This paper presents a novel algorithm for improved shape recovery using polarisation-based photometric stereo. The majority of previous research using photometric stereo involves 3D reconstruction using both the diffuse and specular components of light; however, this paper suggests the use of the specular component only as it is the only form of light that comes directly off the surface without subsurface scattering or interreflections. Experiments were carried out on both real and synthetic surfaces. Real images were obtained using a polarisation-based photometric stereo device while synthetic images were generated using PovRay® software. The results clearly demonstrate that the proposed method can extract three-dimensional (3D) surface information effectively even for concave surfaces with complex texture and surface reflectance.     

空间任意位置回转体的三维重建方法的研究

提出了一种应用几何约束求解的复合回转体的三维重建方法。首先对构成二维三视图的基本图元进行识别和分类提取,再根据回转体的投影特性,建立起回转体的几何约束关系及识别规则,制定出基于回转体投影特性的几何约束求解的算法。运用该算法能够实现对空间任意位置的复合回转体的几何特征约束识别。并且在AutoCADActiveX开发环境下,利用三维约束布尔运算函数,达到三维重建的目的。     

Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging

We describe a computational method for depth extraction of three-dimensional (3D) objects using block matching for slice images in synthetic aperture integral imaging (SAII). SAII is capable of providing high-resolution 3D slice images for 3D objects because the picked-up elemental images are high-resolution ones. In the proposed method, the high-resolution elemental images are recorded by moving a camera; a computational reconstruction algorithm based on ray backprojection generates a set of 3D slice images from the recorded elemental images. To extract depth information of the 3D objects, we propose a new block-matching algorithm between a reference elemental image and a set of 3D slice images. The property of the slices images is that the focused areas are the right location for an object, whereas the blurred areas are considered to be empty space; thus, this can extract robust and accurate depth information of the 3D objects. To demonstrate our method, we carry out the preliminary experiments of 3D objects; the results indicate that our method is superior to a conventional method in terms of depth-map quality.     

Flexible three-dimensional measurement technique based on a digital light processing projector

A new method of 3D measurement based on a digital light processing (DLP) projector is presented. The projection model of the DLP projector is analyzed, and the relationship between the fringe patterns of the DLP and the fringe strips projected into the 3D space is proposed. Then the 3D shape of the object can be obtained by this relationship. Meanwhile a calibration method for this model is presented. Using this calibration method, parameters of the model can be obtained by a calibration plate, and there is no requirement for the plate to move precisely. This new 3D shape measurement method does not require any restrictions as that in the classical methods. The camera and projector can be put in an arbitrary position, and it is unnecessary to arrange the system layout in parallel, vertical, or other stringent geometry conditions. The experiments show that this method is flexible and is easy to carry out. The system calibration can be finished quickly, and the system is applicable to many shape measurement tasks.     

Hybrid method combining orthogonal projection Fourier transform profilometry and laser speckle imaging for 3D visualization of flow profile

This paper reports a straightforward technique for three-dimensional (3D) visualization of a flow profile by a hybrid algorithm combining Fourier transform orthogonal fringe projection and laser speckle imaging techniques. The use of orthogonal projection aims to suppress the zero order allowing surface reconstruction with high spatial resolution and accuracy while analyzing the intensity fluctuations of diffuse backscattered laser light providing 2D flow information. Once both are achieved, 3D flow visualization can be displayed. The method is experimentally validated first with a plastic tube filled with scattering liquid (milk) running at various controlled flow rates and then with the tube embedded under scattering layers (chicken breast) of varying thickness. The system includes a single, common camera, a commercial projector (profilometry channel), a laser light source (flow channel), and a computer station. In addition, orthogonal projection processing was combined with Hilbert transform, increasing the visualization and resolution of the measured flow profile.     

基于多视图立体视觉的沙堆三维尺寸测量研究

利用从运动中恢复结构方法(SFM),提出了一种基于多视图立体视觉的沙堆三维重建及三维尺寸测量方法。首先根据SFM方法的求解不稳定特点,结合光束平差法对SFM求解过程进行分析及优化;其次针对SFM重建结果为稀疏点云的问题,利用基于面片的稠密重建算法重新生成稠密的三维点云,再利用泊松算法对密集点云进行三维曲面重建;最后获得模型的三维尺寸信息。对某建筑工地的沙堆进行了三维尺寸的测量实验,实验结果验证了该方法的有效及可行性,提高了重建能力及精度,同时考虑了目标实际测量误差与重建误差,能够满足实际智能测量的应用需求。     

伪随机阵列和 Harris角测量在视觉检测中的应用

在三维视觉场景重构过程中,一个难题就是场景图像上的坐标点的匹配问题。在工业检测中,通常解决该问题的方法是采用结构光主动视觉技术,如点结构光、线结构光扫描法以及伪随机编码结构光法等。但是要想用一幅图象在三维欧氏空间中重构三维场景,有效的方法是采用伪随机编码结构光照明主动视觉技术。该方法利用编码结构光照明被测场景,利用编码的窗口特性,使场景被测表面每一个特征点都具有唯一的代码而唯一地被辨识。而图像的特征点提取可以采用简单而稳定的Harris角测量。     

立体视觉曲面重建与系统误差分析

采用立体视觉空间曲面重建技术对三维曲面表面成像进行边缘提取、图像匹配、匹配点空间位置计算等步骤,得到三维曲面表面点的空间位置,利用空间点信息对三维曲面形状进行重建,恢复曲面三维形状;并讨论了立体视觉系统的摄像机分辨率、测量范围和摄像机间距等参数之间的关系.利用该方法对堆积物表面形状及体积进行测量实验结果表明,该方法能准确、快速、方便地给出三维曲面的形状.     

Three-dimensional measurement of a gas flow temperature field using far-infrared band CT techniques

Emission spectral tomography (EST) can be utilized to reconstruct three-dimensional (3D) physical parameter distributions of gas flow fields. Mostly, the radiant energy of the visual and near-infrared bands is received by a video camera in EST, so it is difficult to examine a low/medium-temperature gas flow field by normal EST. However, the far-infrared radiant energy of a low/medium-temperature gas flow field is strong enough to be received by a far-infrared detector. Based on EST, a far-infrared band computed tomography (FICT) approach is proposed that focuses on far-infrared spectral emission and band emission tomography. Both low- and medium-temperature blackbody furnaces were adopted to calibrate the relation between infrared thermal image intensity and radiant exitance. The 3D temperature reconstruction of an alcohol blow lamp was carried out. According to the results of multiple measurements, the relative error of the FICT approach is less than 20%. The experimental results prove the feasibility of the FICT approach.     

一种提高双目视觉测量精度的逐步逼近方法

针对空间坐标对图象平面坐标的非线性光学映射关系,本文提出了逐步逼近实现３－Ｄ空间坐标计算的测量方法。该方法对摄象机的摆放姿态与双目传感器的装配精度要求较低,可去除介质折射产生的坐标计算误差。结合局部标定法,对摄象机光学系统的畸变误差进行校正。实验数据表明,在对双目传感器不提出较高要求的测量条件下,测量结果令人满意。     

基于投影重建的增强现实虚实注册方法研究

提出一种改进的、基于目标场景投影重建的增强现实虚实注册方法.方法分为两个阶段,离线阶段,对目标场景进行三维重建,恢复出目标场景的三维结构;实时阶段,求解摄像机与已知三维场景的变换关系,完成三维注册.实验结果证实了此法的可行性与有效性,与传统方法相比,该方法具有更加精确的注册效果.     

Multispectral processing without spectra

It is often the case that multiplications of whole spectra, component by component, must be carried out,for example when light reflects from or is transmitted through materials. This leads to particularly taxing calculations, especially in spectrally based ray tracing or radiosity in graphics, making a full-spectrum method prohibitively expensive. Nevertheless, using full spectra is attractive because of the many important phenomena that can be modeled only by using all the physics at hand. We apply to the task of spectral multiplication a method previously used in modeling RGB-based light propagation. We show that we can often multiply spectra without carrying out spectral multiplication. In previous work [J. Opt. Soc. Am. A 11, 1553 (1994)] we developed a method called spectral sharpening, which took camera RGBs to a special sharp basis that was designed to render illuminant change simple to model. Specifically, in the new basis, one can effectively model illuminant change by using a diagonal matrix rather than the 3 x 3 linear transform that results from a three-component finite-dimensional model [G. Healey and D. Slater, J. Opt. Soc. Am. A 11, 3003 (1994)]. We apply this idea of sharpening to the set of principal components vectors derived from a representative set of spectra that might reasonably be encountered in a given application. With respect to the sharp spectral basis, we show that spectral multiplications can be modeled as the multiplication of the basis coefficients. These new product coefficients applied to the sharp basis serve to accurately reconstruct the spectral product. Although the method is quite general, we show how to use spectral modeling by taking advantage of metameric surfaces, ones that match under one light but not another, for tasks such as volume rendering. The use of metamers allows a user to pick out or merge different volume structures in real time simply by changing the lighting.     

Real-time tricolor phase measuring profilometry based on CCD sensitivity calibration

A real-time tricolor phase measuring profilometry (RTPMP) based on charge coupled device (CCD) sensitivity calibration is proposed. Only one colour fringe pattern whose red (R), green (G) and blue (B) components are, respectively, coded as three sinusoidal phase-shifting gratings with an equivalent shifting phase of 2π/3 is needed and sent to an appointed flash memory on a specialized digital light projector (SDLP). A specialized time-division multiplexing timing sequence actively controls the SDLP to project the fringe patterns in R, G and B channels sequentially onto the measured object in one over seventy-two of a second and meanwhile actively controls a high frame rate monochrome CCD camera to capture the corresponding deformed patterns synchronously with the SDLP. So the sufficient information for reconstructing the three-dimensional (3D) shape in one over twenty-four of a second is obtained. Due to the different spectral sensitivity of the CCD camera to RGB lights, the captured deformed patterns from R, G and B channels cannot share the same peak and valley, which will lead to lower accuracy or even failing to reconstruct the 3D shape. So a deformed pattern amending method based on CCD sensitivity calibration is developed to guarantee the accurate 3D reconstruction. The experimental results verify the feasibility of the proposed RTPMP method. The proposed RTPMP method can obtain the 3D shape at over the video frame rate of 24 frames per second, avoid the colour crosstalk completely and be effective for measuring real-time changing object.