On minimizing maximum errors

It is shown how a previously published control problem by A.G. Parlos (1988) formulated using ellipsoidal set-theoretic control synthesis techniques can be formulated and solved using l¹ optimal control theory. A complete solution is furnished to the problem. It avoids the difficulties of parameter optimization     

立体视频对象分割及其三维重建算法研究*

为更加有效分析立体视频对象,本文提出了一种基于离散冗余小波变换的立体视频对象分割算法,首先采用离散冗余小波变换提取特征点结合DT网格技术的视差估计方法,获得了可靠的视差场,再利用视差信息对立体视频中静止对象进行分割。对于立体视频序列中的运动对象,采用离散冗余小波提取运动区域的方法进行分割。实验结果表明,本算法对有重叠的多视频对象具有较好的分割效果,可同时分割静止物体和运动物体,具有较好的精确性和鲁棒性。对于分割出的立体视频对象,结合深度信息对其进行三维重建,得到较好的三维效果。     

基于立体视觉的三维重建算法

针对PMVS(patch multi-view stereo)算法在三维重建过程中容易出现重建表面不够光滑和连续,某些区域与真实物体的形状有偏差,以及在片面扩展时算法的空间和时间复杂度非常高,在处理高分辨率图像时需要付出巨大的时间和空间代价等问题,提出了一种加入法向调整的PMVS改进算法,使重建出的表面在某些细节部位更加符合真实物体形状,同时通过采用多分辨率分级重建的策略在一定程度上缩短了算法的运行时间,提高了重建效率。通过实验表明了改进后的算法的准确性和高效性。     

双目立体视觉的三维人脸重建方法

创建逼真的三维人脸模型始终是一个极具挑战性的课题.随着三维人脸模型在虚拟现实、视频监控、三维动画、人脸识别等领域的广泛应用,三维人脸重建成为计算机图像学和计算机视觉领域的一个研究热点.针对这一问题,提出一种基于双目立体视觉的三维人脸重建方法,重建过程中无需三维激光扫描仪和通用人脸模型.首先利用标定的2台摄像机获取人脸正面图像对,通过图像校正使图像对的极线对齐并且补偿摄像机镜头的畸变;在立体匹配方面,选择具有准确可靠视差的人脸边缘特征点作为种子像素,以种子像素的视差作为区域生长的视差,在外极线约束、单调性约束以及对应匹配的边缘特征点的约束下,进行水平扫描线上的区域生长,从而得到整个人脸区域的视差图,提高了对应点匹配的速度和准确度;最后,根据摄像机标定结果和立体匹配生成的视差图计算人脸空间散乱点的三维坐标,对人脸的三维点云进行三角剖分、网格细分和光顺处理.实验结果表明,该方法能够生成光滑、逼真的三维人脸模型,证明了该算法的有效性.     

Feature-based RGB-D camera pose optimization for real-time 3D reconstruction

Computational Visual Media - In this paper we present a novel feature-based RGB-D camera pose optimization algorithm for real-time 3D reconstruction systems. During camera pose estimation, current...     

用单数码相机实现物体表面的三维重建

根据由运动重建物体结构的原理,设计了一个简便易操作的三维重建系统,具体做法是:先用张氏标定法求得内参数矩阵,然后在两个不同的未知位置拍摄物体得到两幅图像,经立体匹配后,利用图像特征点的对应关系求解基本矩阵和本质矩阵,分解本质矩阵获得两个拍摄位置确定的摄像机运动参数(旋转矩阵和平移向量),进而求出相机在两个位置的投影矩阵,最后用三角法计算出物体表面特征点的三维坐标并在OpenGL中重建物体表面.和传统的立体视觉系统相比,本系统只需要一台数码相机和平面方格模板就可以实现三维重建,因此适用于普通相机用户.     

Fusing multiview and photometric stereo for 3D reconstruction under uncalibrated illumination

We propose a method to obtain a complete and accurate 3D model from multiview images captured under a variety of unknown illuminations. Based on recent results showing that for Lambertian objects, general illumination can be approximated well using low-order spherical harmonics, we develop a robust alternating approach to recover surface normals. Surface normals are initialized using a multi-illumination multiview stereo algorithm, then refined using a robust alternating optimization method based on the l(1) metric. Erroneous normal estimates are detected using a shape prior. Finally, the computed normals are used to improve the preliminary 3D model. The reconstruction system achieves watertight and robust 3D reconstruction while neither requiring manual interactions nor imposing any constraints on the illumination. Experimental results on both real world and synthetic data show that the technique can acquire accurate 3D models for Lambertian surfaces, and even tolerates small violations of the Lambertian assumption.     

Wireless smart camera network for real-time human 3D pose reconstruction

A multiple-camera system for 3D pose reconstruction is presented. First, body parts of the user are detected. Each camera has a single-instruction multiple-data (SIMD) processor used to perform this heavy-load image processing task. The detected hand and head candidate positions are then transmitted wirelessly from each camera to a central processor using a low-power ZigBee network. Finally, the 3D pose reconstruction is performed at the central processor by combining the data in a probabilistic manner.     

3D map reconstruction using a monocular camera for smart cities

Large-scale high-resolution three-dimensional (3D) maps play a vital role in the development of smart cities. In this work, a novel deep learning-based multi-view-stereo method is proposed for reconstructing the 3D maps in large-scale urban environments by exploiting a monocular camera. Compared with other existing works, the proposed method can perform 3D depth estimation more efficiently in terms of computational complexity and graphics processing unit memory usage. As a result, the proposed method can practically perform depth estimation for each pixel before generating 3D maps for even large-scale scenes. Extensive experiments on the well-known DTU dataset and real-life data collected on our campus confirm the good performance of the proposed method.

     

基于4目阵列的计算机视觉三维重建算法

目前计算机视觉三维重建方法因需布置和标定摄像机环形拍摄场或者需要结构光而存在应用局限性问题,且算法不稳定。为此提出一种将摄像机阵列和图像配准有机结合的4目阵列重建算法,该算法不需要结构光和现场标定摄像机。经过基于包含光照和阴影的复杂室内仿真图像的实验表明,该方法能稳定有效地进行密集点云重建,且能克服现有重建方法的应用局限性与不稳定等缺陷。     

A new approach to 3D reconstruction without camera calibration

In this paper, we present a new approach for 3D scene reconstruction based on projective geometry without camera calibration. Previous works use at least six points to build two projective reference planes. Our contribution is to reduce the number of reference points to four by exploiting some geometrical shapes contained in the scene. The first implemented algorithm allows the reconstruction of a fourth point on each reference plane. The second algorithm is devoted to the 3D reconstruction. We obtained the expected good results and the proposed method is to equip a mobile robot moving in a structured environment.     

Robust refinement methods for camera calibration and 3D reconstruction from multiple images

This paper proposes robust refinement methods to improve the popular patch multi-view 3D reconstruction algorithm by Furukawa and Ponce (2008). Specifically, a new method is proposed to improve the robustness by removing outliers based on a filtering approach. In addition, this work also proposes a method to divide the 3D points in to several buckets for applying the sparse bundle adjustment algorithm (SBA) individually, removing the outliers and finally merging them. The residuals are used to filter potential outliers to reduce the re-projection error used as the performance evaluation of refinement. In our experiments, the original mean re-projection error is about 47.6. After applying the proposed methods, the mean error is reduced to 2.13.     

Real-time stereo matching using memory-efficient Belief Propagation for high-definition 3D telepresence systems

New generations of telecommunications systems will include high-definition 3D video that provides a telepresence feeling. These systems require high-quality depth maps to be generated in a very short time (very low latency, typically about 40 ms). Classical Belief Propagation algorithms (BP) generate high-quality depth maps but they require huge memory bandwidths that limit low-latency implementations of stereo-vision systems with high-definition images.This paper proposes a real-time (latency inferior to 40 ms) high-definition (1280 × 720) stereo matching algorithm using Belief Propagation with good immersive feeling (80 disparity levels). There are two main contributions. The first is an improved BP algorithm with pixel classification that outperforms classical BP while reducing the number of memory accesses. The second is an adaptive message compression technique with a low performance penalty that greatly reduces the memory traffic. The combination of these techniques outperforms classical BP by about 6.0% while reducing the memory traffic by more than 90%.     

Time-of-Flight camera based 3D point cloud reconstruction of a car

Modern car wash systems are generally controlled by light barriers and power measurement sensors. These sensors are directly mounted on the movable parts of the system which result in a slow regulation, leading to non-optimal performance, e.g. in terms of energy, water and detergent consumption or regarding the quality of the result.     

On adjustment of stereo parameters in multiview synthesis for planar 3D displays

This paper investigates the impacts of stereo parameters in multiview synthesis for planar 3D display and presents a novel parameter adjustment method for reducing visual discomforts and geometric distortions. The proposed method combines the geometry of stereoscopic capturing system with the comfortable viewing rules for the human vision system in three steps. First, an identically sized representation between the virtual space and the display space is established, and the virtual camera parameters are derived based on the stereo geometry. Second, the scale factor between the physical space and the virtual space is computed based on the depth of focus theory to diminish vergence–accommodation conflicts. Last, the capturing and displaying parameters are adjusted according to the comfortable viewing zone and personal preference. Experimental results demonstrated that a reliable basis for multiview image synthesis and a more comfortable stereo perception can be achieved by applying the proposed method.     

Minimal vision system for linear camera self-calibration and 3D reconstruction using translation platform

Multimedia Tools and Applications - Camera calibration and 3D reconstruction are two crucial steps in computer vision. With the progress of robot and autonomous rover systems, zooming cameras are...     

Evaluation of correspondence errors for stereo

The computation of a scalar correspondence error is the fundamental step in most stereo correspondence algorithms. The quality of the results obtained by the reconstruction algorithm directly depends on the characteristics of such error. We have developed a procedure to evaluate different methods proposed for the computation of the correspondence error. The evaluation is based on exploring the shape of the error surface generated and testing it for uniqueness, isolation and compatibility. The scheme presented makes it possible to recognise the known characteristics of the tested methods for the computation of a correspondence error from the results of the evaluations. Our results show that, for the tested scenes, the evaluation scheme allows us to identify the most appropriate method to compute the correspondence error.     

光度立体技术的物体三维表面重建算法模拟与评价

为了提高基于光度立体法的物体三维表面重建精度,研究了几种常用三维表面重建算法的适用范围.介绍了几种常用重建算法(变分法、金字塔法、代数法)的基本原理及求解方法,指出了表面方向梯度的求解准确度是三维表面重建过程中的难点.在此基础上建立了朗伯半球体模型和实际拍摄的玻璃灯罩,从重建速度、重建精度等方面对几种算法进行了比较和评价.最后通过实验模拟和算法性能评价,表明了常用算法的重建精确度有限,并且时三维重建今后的研究进行了展望.     

Automatic 3D model reconstruction of cutting tools from a single camera

Collision detection by machining simulation requires the 3D models of rotating cutters. However, the 3D models of a cutter and holder are not always available. In this paper, a new method is proposed to design an automatic vision-based 3D modeling system, which is able to quickly reconstruct the 3D model of a cutter and holder when they are installed onto the spindle. Only a single camera is mounted on the machine tool to capture the image of the rotating cutter and holder. By viewing the rotating cutter and holder as an object of surface of revolution, the contour of the imaged cutter and holder can be used to reconstruct the 3D model as a stack of circular cross-sections. Then the complete generating function of the cutter and holder can be recovered from the cross-sections. Finally, the 3D model of the cutter is built by rotating the generating function around the spindle axis. The effectiveness and accuracy of the proposed method are verified by experiments on-machine using 12 kinds of cutters and holders, which can satisfy the requirement of collision detection.