图像测速法的摄像机标定技术

针对漂浮在空气中或者液体中的粒子的速度测量,提出了一种基于双目视觉的测量方法。采用两个光轴相互垂直的CCD摄像机,分布在测量腔体的左右两侧。结合系统的几何结构特点,两个CCD摄像机分别标定,将标定模型方程转化为多项式形式,利用最小二乘原则获取平面模型标定参数,然后再利用公垂线距离最短原则实现三维坐标测量。实验给出了三维坐标的偏差分布图,证明这是一种实用有效快速的标定方法。     

深空背景下基于Delaunay三角剖分的多成像器目标对应算法

针对深空背景下,目标距离成像器较远,目标在多个成像器平面呈弱小目标,目标点之间的形状及灰度特征没有明显区别的现状,提出了基于目标点之间形成的几何组合来完成目标点在不同成像平面对应的算法.该算法首先对各个成像器目标检测后获取的目标点集根据成像器间的姿态信息进行旋转补偿,然后对补偿后的目标点集进行Delaunay三角剖分,...     

Singular-value decomposition for through-focus imaging systems

Singular-value decomposition (SVD) of a linear imaging system gives information on the null and measurement components of object and image and provides a method for object reconstruction from image data. We apply SVD to through-focus imaging systems that produce several two-dimensional images of a three-dimensional object. Analytical expressions for the singular functions are derived in the geometrical approximation for a telecentric, laterally shift-invariant system linear in intensity. The modes are evaluated numerically, and their accuracy confirmed. Similarly, the modes are derived and evaluated for a continuous image representing the limit of a large number of image planes.     

First-order algorithm with three clusters of optical flow vectors

The first-order algorithm is an algorithm for recovering the motion parameters from a single optical flow field. It compares the spatial derivatives, to first order, of the optical flow field obtained from two different parts of the field of view and obtains a linear constraint on the direction of the translational velocity. We modify this algorithm to incorporate the spatial derivatives, to first order, of the optical flow field obtained from a third part of the field of view, and thereby obtain two further linear constraints on the direction of the translational velocity. Only two linear constraints are required to identify the direction of the translational velocity. Therefore, with three linear constraints, there are three ways of estimating the direction of the translational velocity. Although all three estimates are derived from the same set of information, we show that the three estimates are not, in general, equally stable. We assume that each cluster of flow vectors arises from a plane in the environment and show that a linear constraint is most stable when it emanates from a pair of parallel planes, with the camera between them. We also identify the relative orientations of the clusters of flow vectors that maximize and minimize the stability of the linear constraint that they give rise to. © 1996 John Wiley & Sons, Inc.     

Information contained in the motion field of lines and the cooperation between motion and stereo

We investigate the relationships that exist between the three-dimensional structure and kinematics of a line moving rigidly in space and the two-dimensional structure and kinematics (motion field) of its image in one or two cameras. We establish the fundamental equations that relate its three-dimensional motion to its observed image motion. We show how this motion field can be estimated from a line-based token tracker. We then assume that stereo matches have been established between image segments and show how the estimation of the motion field in the two images can be used to compute part of the kinematic screw of the corresponding 3D line. The equations are linear and if several lines belong to the same object provide a very simple way to estimate the full kinematic screw of that object. Finally, we show how the motion field can constrain the stereo matches by establishing necessary conditions that must be satisfied by the motion field of segments which are images of lines belonging to the same object. Only part of this theory has been implemented yet. This part uses Kalman filtering. Several experimental results using synthetic and real data are presented.     

Depth extraction by use of a rectangular lens array and one-dimensional elemental image modification

Stereo matching, a technique for acquiring depth information from many planar images obtained by several cameras, was developed several decades ago. Recently a novel depth-extraction technique that uses a lens array instead of several cameras has attracted much attention because of the advantages offered by its compact system configuration. We present a novel depth-extraction method that uses a lens array consisting of vertically long rectangular lens elements. The proposed method rearranges the horizontal positions of the pixels from the collection of perspective images while it leaves the vertical positions of the pixels unchanged. To these rearranged images we apply a correlation-based multibaseline stereo algorithm in properly modified form. The main feature of the proposed method is the inverse dependency of the disparity in depth between horizontal and vertical directions. This inverse dependency permits the extraction of exact depth from extremely periodically patterned object scenes and reduces quantization error in the depth extraction.     

Surface segmentation based on the luminance and color statistics of natural scenes

The luminance and color of surfaces in natural scenes are relatively independent under certain linear transformations, with the luminance of a surface providing little information about the color of that surface, and vice versa. However, differences in luminance between two locations in a natural scene remain strongly associated with differences in color. We used the statistics of the spatiochromatic structure of natural scenes as the priors for a Bayesian model that decides whether or not two points within an image fall on the same surface. This model provides a biologically plausible algorithm for surface segmentation that models observer segmentations well.     

基于视觉辅助定位的机械臂运动学参数辨识研究

标定机器臂的运动学参数可以有效提高机械臂的绝对定位精度。针对一般平面约束标定方法往往通过手动示教获取测量数据,效率低,提出一种基于视觉辅助定位约束平面的机械臂运动学参数辨识方法。为了弥补双目视觉视场范围狭小的弊端,在约束平面上粘贴3个靶点,以此将对平面的定位等效成对靶点的定位。应用双目视觉系统提取靶点中心并进行立体匹配,得到靶点在机械臂基坐标系下的三维位置信息;同时构建靶点坐标系,以此规划出按一定规律分布的约束点;为了进一步提高标定精度,建立双平面约束误差模型,通过两垂直平面上任意非共线的3个点得到一系列法向量,每一对法向量的数量积为0,即增加了约束方程;利用机械臂对相互垂直的两约束平面自动进行接触式测量,通过改进的最小二乘法辨识出真实的运动学参数误差。实验结果表明,基于双平面约束误差模型,修正运动学参数后,机械臂绝对位置精度由1.234 mm提高到了0.453 mm。该方法实现了数据的自动化测量,大大提高了标定效率,为机械臂批量标定提供了参考,具有工程意义。     

An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a temporal slice image can be obtained for pedestrian counting without the need for visual tracking. Only ten low level features are extracted from the input image to establish a feature vector. As a result, our algorithm is more efficient and accurate than existing methods. Pedestrians in the temporal slice image are then located by the two-stage detection algorithm, which is largely based on support vector machine and affinity propagation clustering. Moreover, a novel algorithm is proposed to determine the moving directions of pedestrians by comparing the centers of them in two temporal slice images. Extensive experiments reveal that our system achieves satisfaction performances in terms of both robustness and efficiency.     

Wavelet power spectrum-based autofocusing algorithm for time delayed and integration charge coupled device space camera

A novel autofocusing algorithm using the directional wavelet power spectrum is proposed for time delayed and integration charge coupled device (TDI CCD) space cameras, which overcomes the difficulty of focus measure for the real-time change of imaging scenes. Using the multiresolution and band-pass characteristics of wavelet transform to improve the power spectrum based on fast Fourier transform (FFT), the wavelet power spectrum is less sensitive to the variance of scenes. Moreover, the new focus measure can effectively eliminate the impact of image motion mismatching by the directional selection. We test the proposed method's performance on synthetic images as well as a real ground experiment for one TDI CCD prototype camera, and compare it with the focus measure based on the existing FFT spectrum. The simulation results show that the new focus measure can effectively express the defocused states for the real remote sensing images. The error ratio is only 0.112, while the prevalent algorithm based on the FFT spectrum is as high as 0.4. Compared with the FFT-based method, the proposed algorithm performs at a high reliability in the real imaging experiments, where it reduces the instability from 0.600 to 0.161. Two experimental results demonstrate that the proposed algorithm has the characteristics of good monotonicity, high sensitivity, and accuracy. The new algorithm can satisfy the autofocusing requirements for TDI CCD space cameras.     

Image rectification for stereoscopic visualization

This paper proposes an approach to rectifying two images of the same scene captured by cameras at general positions so that the results form a stereo pair that satisfies the constraints of the stereoscopic visualization platforms. This is unlike conventional image rectification research that primarily focuses on making stereo matching easier but pays little attention to 3D viewing. The novel derivation of the rectification algorithm also has an intuitive physical meaning that is not available from conventional approaches. Practical issues related to wide-baseline rectification and operation range of the proposed method are analyzed. Both simulated and real data experiments are used to assess the performance of the proposed algorithm.     

Estimating three-dimensional vehicle motion in an outdoor scene using stereo image sequences

We propose a motion estimation system that uses stereo image pairs as the input data. To perform experimental work, we also obtain a sequence of outdoor stereo images taken by two metric cameras. The system consists of four main stages, which are (1) determination of point correspondences on the stereo images, (2) correction of distortions in image coordinates, (3) derivation of 3D point coordinates from 2D correspondences, and (4) estimation of motion parameters based on 3D point correspondences. For the first stage of the system, we use a four-way matching algorithm to obtain matched point on two stereo image pairs at two consecutive time instants (t_i and t_{i + 1}). Since the input data are stereo images taken by cameras, it has two types of distortions, which are (i) film distortion and (ii) lens distortion. These two distortions must be corrected before any process can be applied on the matched points. To accomplish this goal, we use (i) bilinear transform for film distortion correction and (ii) lens formulas for lens distortion correction. After correcting the distortions, the results are 2D coordinates of each matched point that can be used to derive 3D coordinates. However, due to data noise, the calculated 3D coordinates to not usually represent a consistent rigid structure that is suitable for motion estimation; therefore, we suggest a procedure to select good 3D point sets as the input for motion estimation. The procedure exploits two constraints, rigidity between different time instants and uniform point distribution across the object on the image. For the last stage, we use an algorithm to estimate the motion parameters. We also wish to know what is the effect of quantization error on the estimated results; therefore an error analysis based on quantization error is performed on the estimated motion parameters. In order to test our system, eight sets of stereo image pairs are extracted from an outdoor stereo image sequence and used as the input data. The experimental results indicate that the proposed system does provide reasonable estimated motion parameters.     

Unsupervised clustering approaches to color classification for color-based image code recognition

Color-vision-based applications for mobile phones has become a subject of special interest lately. It would be interesting to investigate an unsupervised, adaptive, and fast algorithm that can classify color components into color clusters. We propose a hierarchical clustering approach using a single-linkage algorithm and a k-means clustering approach to color classification for color-based image code recognition in mobile computing environments. We also measured the performance of the proposed algorithms by color channel stretch, which is a simple color-correction method. Experimental results show that the single-linkage method is more robust than previous algorithms used in experiments with varying cameras and print materials. In particular the k-means-based method with color channel stretching has the highest performance and is the most robust under varying environment conditions such as illuminants, cameras, and print materials.     

基于稀疏激光点云数据和单帧图像融合的三维重构算法

由于激光雷达获取的深度数据非常稀疏,为了能够将深度数据与图像数据重构出稠密三维深度图,本文提出了基于稀疏激光点云数据和单帧图像融合的三维重构算法。该方法首先使用点直方图特征有效地选择对应于目标的点数据并消除体素中的非相似点;然后,使用高斯过程回归对局部深度数据建模,并通过插值获得三维深度数据,本文算法获得的三维深度点更接近基准值,并保持了目标的局部形状特征;最后,利用马尔科夫随机场对图像灰度数据和三维插值点进行融合来构建三维深度图。仿真实验结果表明:相比现有基于激光雷达数据和单目图像数据的三维重建算法,本文提出的算法将大大提升算法的鲁棒性与重构的准确度,可辅助用于复杂的城市场景中车辆的无人驾驶。     

Influence of unparallel grating planes in talbot interferometry with cross gratings of different spatial frequencies in two directions

The effects of an arbitrary small inclination between two cross gratings on the moiré fringes in Talbot interferometry are discussed when the frequencies of the grating differ in two perpendicular directions. We show that the small angles, alpha and beta, by which the beam-splitter cross grating is rotated around the two axes parallel to the two perpendicular line directions of the cross grating, have a greater influence on the moiré fringes with cross gratings than that with one-dimensional gratings. A simple and practical detection method for the angles between the two unparallel grating planes in Talbot interferometry is also proposed. The theoretical analyses are proved by experimental results.     

Photogrammetric endoscope for measurement of inner cylindrical surfaces using fringe projection

We present a photogrammetric endoscope to measure three dimensional (3D) shapes of inner cylindrical surfaces by fringe projection. The basic configuration includes two identical cameras aligned with the optical axis and facing each other, conical lenses, and a 360 degrees helical fringe projector. The helical fringe pattern is phase shifted and acquired by both cameras. The phase patterns are used to acquire data from the surface in a regular cylindrical mesh. A prototype was built, calibrated, and tested. We present the results and an application to inspect internal welding seams and misalignment of welded joints in 150 mm (6 in.) diameter pipelines.     

善用RAW格式存储痕迹物证数码照片

目前,数码相机采用的存储格式主要有RAW、JPEG、TIFF。相机的传感器在曝光后获得的信息可以保持原始状态存储在存储卡中,形成RAW格式文件,以后再用专门软件处理,也可以直接在相机内经机内软件处理形成JPEG或TIFF格式文件的图像。后二种方法比较快捷,但有时会损失一些影像细节;而以RAW格式存储的拍摄数据经专门软件后处理,往往可以获得一些有用的影像细节,对痕迹物证照相很有价值;本文对此简明阐述。     

Novel method of calibration with restrictive constraints for stereo-vision system

Regarding the calibration of a stereo vision measurement system, this paper puts forward a new bundle adjustment algorithm based on the stereo vision camera calibration method. Multiple-view geometric constraints and a bundle adjustment algorithm are used to optimize the inner and outer parameters of the camera accurately. A fixed relative constraint relationship between cameras is introduced. We have improved the normal equation construction process of the traditional bundle adjustment method, so that each iteration process occurs just outside the parameters of two images that are taken by a camera that has been optimized to better integrate two cameras bound together as one camera. The relationship between the fixed relative constraints can effectively increase the number of superfluous observations of the adjustment system and optimize higher accuracy while reducing the dimension of the normal matrix; it means that each iteration will reduce the time required. Simulation and actual experimental results show the superior performance of the proposed approach in terms of robustness and accuracy, and our approach also can be extended to stereo-vision system with more than two cameras.     

几何约束下曲面场景的立体匹配迭代算法

使用对极约束和同形映射两种几何约束,通过采用面积检测、一致性约束误差检测、概率筛选规则和对称优化等策略,成功地实现了曲面场景图像的特征点匹配.该方法未使用任何与灰度相关的信息和与场景相关的约束,极大地提高了方法的实用性和鲁棒性.整个匹配过程快速有效,并在不同的弱标定关系已知的真实图像数据上成功地得到实现.