3-D shape reconstruction in an active stereo vision system using genetic algorithms

The recovery of 3-D shape information (depth) using stereo vision analysis is one of the major areas in computer vision and has given rise to a great deal of literature in the recent past. The widely known stereo vision methods are the passive stereo vision approaches that use two cameras. Obtaining 3-D information involves the identification of the corresponding 2-D points between left and right images. Most existing methods tackle this matching task from singular points, i.e. finding points in both image planes with more or less the same neighborhood characteristics. One key problem we have to solve is that we are on the first instance unable to know a priori whether a point in the first image has a correspondence or not due to surface occlusion or simply because it has been projected out of the scope of the second camera. This makes the matching process very difficult and imposes a need of an a posteriori stage to remove false matching.In this paper we are concerned with the active stereo vision systems which offer an alternative to the passive stereo vision systems. In our system, a light projector that illuminates objects to be analyzed by a pyramid-shaped laser beam replaces one of the two cameras. The projections of laser rays on the objects are detected as spots in the image. In this particular case, only one image needs to be treated, and the stereo matching problem boils down to associating the laser rays and their corresponding real spots in the 2-D image. We have expressed this problem as a minimization of a global function that we propose to perform using Genetic Algorithms (GAs). We have implemented two different algorithms: in the first, GAs are performed after a deterministic search. In the second, data is partitioned into clusters and GAs are independently applied in each cluster. In our second contribution in this paper, we have described an efficient system calibration method. Experimental results are presented to illustrate the feasibility of our approach. The proposed method yields high accuracy 3-D reconstruction even for complex objects. We conclude that GAs can effectively be applied to this matching problem.     

Pattern codification strategies in structured light systems

Coded structured light is considered one of the most reliable techniques for recovering the surface of objects. This technique is based on projecting a light pattern and viewing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be easily found. The decoded points can be triangulated and 3D information is obtained. We present an overview of the existing techniques, as well as a new and definitive classification of patterns for structured light sensors. We have implemented a set of representative techniques in this field and present some comparative results. The advantages and constraints of the different patterns are also discussed.     

A structured light vision system for out-of-plane vibration frequencies location of a moving web

In this paper, we address the problem of the detection of out-of-plane web vibrations by means of a single camera and a laser dots pattern device. We have been motivated by the important economical impact of web vibrations phenomena which occur in winding/unwinding systems. Among many sources of disturbances, out-of-plane vibrations of an elastic moving web are well-known to be one of the most limiting factors for the velocity in the web transport industry.The new technique we proposed for the contact-less estimation of out-of-plane web vibration properties and during the winding process is the main contribution of this work. As far as we know, this is the first time a technique is proposed to evaluate the vibrations of a moving web with a camera. Vibration frequencies are estimated from distance variations of a web cross-section with respect to the camera.Experiments have been performed on a winding plant for elastic fabric with a web width of 10 cm. Distances from the web surface to the camera have been estimated all along an image sequence and the most significant frequencies have been extracted from the variations of this signal (forced and free vibrations) and compared to those provided with strain gauges and also with a simple elastic string model, in motion.     

结构光视觉引导的焊接机器人系统自标定技术

为实现结构光视觉引导的焊接机器人系统的标定,解决现有标定方法复杂,标定靶标制作要求高等缺点,提出一种基于主动视觉的自标定方法。该标定方法对场景中3个特征点取像,通过精确控制焊接机器人进行5次平移运动,标定摄像机内参数和手眼矩阵旋转部分;通过进行2次带旋转运动,结合激光条在特征点平面的参数方程,标定手眼矩阵平移部分和结构光平面在摄像机坐标系下的平面方程;并针对不同焊枪长度进行修正。在以Denso机器人为主体构建的结构光视觉引导的焊接机器人系统上的测试结果稳定,定位精度可达到±0.93 mm。该标定方法简单,特征选取容易,对焊接机器人系统在实际工业现场的使用有重要意义。     

结构光视觉引导的轨迹跟踪系统的标定技术

为实现机械臂对工业现场三维特征点的跟踪,提出一种基于结构光视觉,六轴机械臂的整体标定方法。利用自制平面靶标求取单映射矩阵,根据张正友标定方法标定相机内参以及对应外参,利用LM算法优化参数,根据激光光条在靶标平面的参数方程和对应的外参标定出激光光平面在相机坐标系下的平面方程,通过求解[AX=XB]方程得到相机坐标系与机械臂末端坐标系的齐次变换矩阵[X],并对特定位姿下的工件偏移进行修正。实际测试表明：静态跟踪误差在±1.2 mm,满足工业现场应用要求。     

A state of the art in structured light patterns for surface profilometry

Shape reconstruction using coded structured light is considered one of the most reliable techniques to recover object surfaces. Having a calibrated projector-camera pair, a light pattern is projected onto the scene and imaged by the camera. Correspondences between projected and recovered patterns are found and used to extract 3D surface information. This paper presents an up-to-date review and a new classification of the existing techniques. Some of these techniques have been implemented and compared, obtaining both qualitative and quantitative results. The advantages and drawbacks of the different patterns and their potentials are discussed.     

Motion capture and human pose reconstruction from a single-view video sequence

We propose a framework to reconstruct the 3D pose of a human for animation from a sequence of single-view video frames. The framework for pose construction starts with background estimation and the performer?s silhouette is extracted using image subtraction for each frame. Then the body silhouettes are automatically labeled using a model-based approach. Finally, the 3D pose is constructed from the labeled human silhouette by assuming orthographic projection. The proposed approach does not require camera calibration. It assumes that the input video has a static background, it has no significant perspective effects, and the performer is in an upright position. The proposed approach requires minimal user interaction.     

Projective reconstruction of all visual primitives

We present a method to simultaneously reconstruct cameras, points, lines, degenerate quadrics and full-rank quadrics from a set of n uncalibrated views of a static scene. Our method is based on the use of Bundle Adjustment to refine an initial reconstruction. During the initialization stage, a novel algorithm was proposed for the conic outline correction in n views. Constrains derived from this algorithm were also integrated in the cost function of Bundle Adjustment to help preserve the right topology of the reconstructed quadrics.     

基于结构光视觉的白车身覆盖件间隙面差测量方法

针对白车身表面覆盖件间隙面差人工测量精度差、效率低等问题,提出了利用结构光视觉测量方法代替人工测量.在间隙特征点识别中,计算光纹中心线上各点的绝对差分值,搜索差分极值点并将该极值点作为特征点;在面差特征点识别中,采用基于离散曲线曲率极值点的特征点定位算法.实验结果表明:间隙面差测量方法测量精度较高,能够满足整车厂对白车身间隙面差测量精度的要求.     

Self-recalibration of a structured light system via plane-based homography

Self-recalibration of the relative pose in a vision system plays a very important role in many applications and much research has been conducted on this issue over the years. However, most existing methods require information of some points in general three-dimensional positions for the calibration, which is hard to be met in many practical applications. In this paper, we present a new method for the self-recalibration of a structured light system by a single image in the presence of a planar surface in the scene. Assuming that the intrinsic parameters of the camera and the projector are known from initial calibration, we show that their relative position and orientation can be determined automatically from four projection correspondences between an image and a projection plane. In this method, analytical solutions are obtained from second order equations with a single variable and the optimization process is very fast. Another advantage is the enhanced robustness in implementation via the use of over constrained systems. Computer simulations and real data experiments are carried out to validate our method.     

基于机器视觉的人工光植物工厂植物生长状况监测系统

设计了一种基于机器视觉的人工光植物工厂植物生长状况监测系统,主要利用机器视觉技术对植物工厂中植物生长进行无损监测,获取植物的生长信息.同时解决了针对LED偏色光情况下,获取植物前景图像不完整的问题.利用该系统可以快速、准确地获取植物生长的叶面积等参数,实现植物生长状况的实时监测,为植物生产过程中有关作业的自动化奠定了基础,具有广阔的应用前景.     

Modular architecture for custom-built systems oriented to real-time computer vision: Application to color recognition

This paper presents a modular architecture called DIPSA, which is intended to be used for building custom-made real-time Computer-Vision systems. It consists of four module types and each of them represents a family of circuits that perform specific visual tasks. Our architectural model proposes an algorithm-dependent methodology and makes good results possible using problem oriented solutions. The desired performance is achieved choosing the appropriate modules and connecting them by means of heterogeneous pipeline and concurrence. Additionally, two DIPSA-based hardware systems for real-time Color Recognition are described here.     

Machine vision system for curved surface inspection

This application-oriented paper discusses a non-contact 3D range data measurement system to improve the performance of the existing 2D herring roe grading system. The existing system uses a single CCD camera with unstructured halogen lighting to acquire and analyze the shape of the 2D shape of the herring roe for size and deformity grading. Our system will act as an additional system module, which can be integrated into the existing 2D grading system, providing the additional third dimension to detect deformities in the herring roe, which were not detected in the 2D analysis. Furthermore, the additional surface depth data will increase the accuracy of the weight information used in the existing grading system. In the proposed system, multiple laser light stripes are projected into the herring roe and the single B/W CCD camera records the image of the scene. The distortion in the projected line pattern is due to the surface curvature and orientation. Utilizing the linear relation between the projected line distortion and surface depth, the range data was recovered from a single camera image. The measurement technique is described and the depth information is obtained through four steps: (1) image capture, (2) stripe extraction, (3) stripe coding, (4) triangulation, and system calibration. Then, this depth information can be converted into the curvature and orientation of the shape for deformity inspection, and also used for the weight estimation. Preliminary results are included to show the feasibility and performance of our measurement technique. The accuracy and reliability of the computerized herring roe grading system can be greatly improved by integrating this system into existing system in the future.     

嵌入式彩色图像传感器重构系统的设计与实现

为了获取高品质的彩色图像,实现特殊作业现场的图像采集,提出了一种嵌入式彩色CCD图像传感器重构系统的设计方法.通过对图像边界方向的有效判断来完善图像高频区和低频区边界的质量,同时增加三原色之间的耦合性来提高图像清晰度,并且完成了系统的嵌入式底层实现.测试证明:该系统色彩还原效果良好,重构处理时间为34ms,稳定性好,实...     

VICUR: A human-vision-based algorithm for curve reconstruction

In this paper, a new algorithm, named VICUR, is presented for curve reconstruction problem. From a set of unorganized points, the proposed algorithm can construct curves that look natural to human vision. The VICUR algorithm is based on two connectivity criteria: proximity and good continuation from the prominent Gestalt principles of perception. Experimental results are presented to show the effectiveness of VICUR.     

The research of an automatic object reconstruction method based on limit visible region of the laser-scanning vision system

This paper presents an automatic multi-view selection approach for 3D reconstruction by means of a laser scanning vision system. It is realized based on the visual region of the laser scanning vision system. The candidate next best view (NBV) position is obtained by computing the unknown space area according to the limit visual region of the vision system. The final NBV position, which can acquire the maximal visual area, is obtained by comparing the above candidate’s view positions. Experimental results show successful implantation of the proposed view planning method for digitization and reconstruction of freeform objects.     

Computer vision and long short-term memory: Learning to predict unsafe behaviour in construction

Predicting unsafe behaviour in advance can enable remedial measures to be put in place to mitigate likely accidents on construction sites. Prevailing safety studies in construction tend to be retrospective and focus on examining the conditions that contribute to unsafe behaviour from a psychological perspective. While such studies are warranted, they can also not visually comprehend the dynamic and complex conditions that influence unsafe behaviour. In this paper, we aim to contribute to filling this void and, in doing so, combine computer vision with Long-Short Term Memory (LSTM) to predict unsafe behaviours from videos automatically. Our proposed approach for predicting unsafe behaviour is based on: (1) tracking people using a SiamMask; (2) predicting the trajectory of people using an improved Social-LSTM; and (3) predicting unsafe behaviour using Franklin's point inclusion polygon (PNPoly) algorithm. We use the Wuhan metro project as a case to evaluate our approach’s feasibility and effectiveness. Our adopted SiamMask method outperforms current techniques used for tracking people. Additionally, our improved Social-LSTM can achieve higher accuracy on trajectory prediction than other methods (e.g., Social-GAN). The research findings demonstrate that our developed computer vision approach can be used to accurately predict unsafe behaviour on construction sites.     

Adjustable typography: an approach to enhancing low vision text accessibility

Millions of people have low vision, a disability condition caused by uncorrectable or partially correctable disorders of the eye. The primary goal of low vision rehabilitation is increasing access to printed material. This paper describes how adjustable typography, a computer graphic approach to enhancing text accessibility, can play a role in this process, by allowing visually-impaired users to customize fonts to maximize legibility according to their own visual needs. Prototype software and initial testing of the concept is described. The results show that visually-impaired users tend to produce a variety of very distinct fonts, and that the adjustment process results in greatly enhanced legibility. But this initial testing has not yet demonstrated increases in legibility over and above the legibility of highly legible standard fonts such as Times New Roman.     

MOBSY: Integration of vision and dialogue in service robots

Abstract. This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute.     

Determining limits to avoid double vision in an autostereoscopic display: Disparity and image element width

Abstract— The purpose of this study was to investigate the diplopia limits for three‐dimensional stereoscopic content and to determine the main methodological issues when the limits are studied with an autostereoscopic display. One of the main issues regarding stereoscopic content is the structural features that enable the user to see stereo image as a single image. If the depth of the content is not within certain limits, the perceiver cannot see the images three dimensionally and the viewing is uncomfortable. On the other hand, if these limits are followed, the user can stereoscopically fuse the images and see the resulting three‐dimensional image correctly. Some of these limits were tested and guidelines for proper depth values for stereoscopic images will be presented.