五自由度立体视觉平台--目标物体的识别与定位

从立体视觉与机器人控制集成的角度出发,建立了一个主动立体视觉跟踪和定位系统,用于柔性装配线中装配零件的运动跟踪和装配工位的精确定位。讨论了使用立体视觉进行快速目标识别和定位的方法,该方法将颜色分割与基于形状特征相结合,提出采用基于局部图像的HSV阈值分割和形状识别相结合的图像处理方法,该方法经过HSV阈值和形状判据,准确地识别出物体,得到物体的边界和质心。能快速准确地识别出物体并进行定位,满足柔性生产线小规模定制产品装配的要求。最后给出的实验结果验证了该方法的有效性。     

一种嵌入式实时图像跟踪系统设计

该文提出了一套可用于快速视觉信息处理的实时目标跟踪嵌入式视觉系统。系统的硬件设计采用了基于DSP和现场可编程逻辑器件(FPGA)的双处理器结构和基于CMOS的图像采集。软件采用了适于流水线运算的块匹配算法,实现了对目标的快速定位和实时跟踪。     

基于立体视觉运动速度检测系统的研究及实现

介绍了一种基于立体视觉的运动速度检测系统的结构框架。系统在采集卡自带的软件开发包的基础上进行二次软件开发,加入了摄像机标定和图像处理分析部分。整个检测系统主要包括图像采集和运动检测两大环节;涵盖摄像机标定、图像获取及预处理、目标分割、3D定位、速度求取5个功能模块,并具有友好的操作界面,方便用户使用。文章重点针对目标分割和定位中所采用的技术方法展开了讨论。该系统可以具体应用在车辆和游乐设施等的运动速度检测上,在设备的安全运行以及交通监管方面有重要意义。     

基于立体视觉的目标姿态测量技术

基于动态场景分析的计算机视觉系统尤其是对运动目标的运动参数测量已成为计算机视觉研究的热点;建立了基于双目立体视觉的目标姿态测量系统,使用两个摄像机在不同视角对同一目标进行拍摄,采用DLT方法对摄像机标定;对拍摄到的图像进行去噪、滤波,通过立体图像匹配得到特征点在两幅图像中的同名点,姿态参数求解结合DLT算法和立体图像匹配算法,实现了对目标姿态参数的测量,得到了目标的三维姿态信息;实验结果表明,该测量系统结构简单,计算量小,具有较高的测量精度.     

Three-dimensional shape from color photometric stereo

Computer vision systems can be used to determine the shapes of real three-dimensional objects for purposes of object recognition and pose estimation or for CAD applications. One method that has been developed is photometric stereo. This method uses several images taken from the same viewpoint, but with different lightings, to determine the three-dimensional shape of an object. Most previous work in photometric stereo has been with gray-tone images; color images have only been used for dielectric materials. In this paper we describe a procedure for color photometric stereo, which recovers the shape of a colored object from two or more color images of the object under white illumination. This method can handle different types of materials, such as composites and metals, and can employ various reflection models such as the Lambertian, dichromatic, and Torrance-Sparrow models. For composite materials, colored metals, and dielectrics, there are two advantages of utilizing color information: at each pixel, there are more constraints on the orientation, and the result is less sensitive to noise. Consequently, the shape can be found more accurately. The method has been tested on both artificial and real images of objects of various materials, and on real images of a multi-colored object.     

基于双目视觉的运动目标跟踪与测量

在研究融合运动目标位置预测的Mean Shift跟踪算法和双目立体视觉中的空间点定位算法的基础上,基于双目视觉设计了双目立体视觉运动目标跟踪和测量系统,并在所进行的跟踪与测量实验中,提取了运动目标质心的三维坐标序列,实现了对目标深度和速度的测量。     

基于DirectShow的多线程视频采集系统

立体视觉系统是拟人机器人重要组成部分。为满足立体视觉系统的特殊要求，提出了基于DirectShow技术的多线程视频采集系统。该系统实现了同步采集2个USB摄像头数据，具有结构简单、实现方便的特点，是立体视觉开发的良好平台。     

一种基于立体视觉的运动目标检测算法

在目标检测中采用立体视觉方法。首先对立体图像对进行匹配求取场景的视差图,再运用基于视差的背景差分法获得含有运动目标的前景区域,最后根据前景区域的视差和位置分布准确定位各运动目标。立体视觉方法有效解决了单目视觉检测方法中的一些难点问题,可以克服光线的变化和阴影干扰对目标检测带来的影响,在多个目标发生部分遮挡时仍能正确区分各运动目标。     

Fuzzy image processing scheme for autonomous navigation of human blind

The main objective of this work is to develop an electronic travel aid to assist the blinds for obstacle identification in their navigation. This navigation assistance for visually impaired (NAVI) system presented in this paper consists of a single board processing system (SBPS), a vision sensor mounted headgear and a pair of stereo earphones. The image environment in front of the blind is captured by the vision sensor. The image is processed by a new real time image processing scheme using fuzzy clustering algorithms. The processed image is mapped onto a specially structured stereo acoustic patterns and transferred to the stereo earphones in the system. Blind individuals were trained with NAVI system and tested for obstacle identification. Suggestions from the blind volunteers regarding pleasantness and discrimination of sound pattern were also incorporated in the prototype. The proposed processing methodology is found to be effective for object identification and for producing stereo sound patterns in the NAVI system.     

融合深度和颜色信息的图像物体分割算法

讨论立体图对的图像分割问题,提出一种基于深度和颜色信息的图像物体分割算法。该算法首先利用基于聚类的Mean-shift分割算法对目标图像进行适度的过分割,同时借助双目立体视觉算法获取立体图对的稠密深度图,并依据深度不连续性从过分割结果中选取用于继续进行“精致”分割的种子点集,接着对未分配种子标签的区域用图割算法分配标签,并对彼此之间没有深度不连续边界但具有不同标签的相邻区域进行融合。相比于传统图像分割算法,该算法可有效克服过分割和欠分割问题,获取具有一定语义的图像分割结果。相关的对比实验结果验证了该算法的有效性。     

基于立体视觉的目标检测与轨迹预测研究综述

目前基于立体视觉信息的运动目标识别定位、跟踪及轨迹预测是机器视觉领域的研究热点.通过归纳整理相关文献,从双目立体视觉技术、运动目标检测技术、运动目标轨迹预测技术三个方面对基于立体视觉的运动目标检测及轨迹预测进行了概述,分别阐述了相机标定的常见方法、图像特征提取及立体匹配不同算法的适用场景、各运动目标检测方法的优缺点、常...     

基于主动视觉和超声的机器人目标跟踪系统

运动目标跟踪技术是未知环境下移动机器人研究领域的一个重要研究方向。该文提出了一种基于主动视觉和超声信息的移动机器人运动目标跟踪设计方法,利用一台SONY EV-D31彩色摄像机、自主研制的摄像机控制模块、图像采集与处理单元等构建了主动视觉系统。移动机器人采用了基于行为的分布式控制体系结构,利用主动视觉锁定运动目标,通过超声系统感知外部环境信息,能在未知的、动态的、非结构化复杂环境中可靠地跟踪运动目标。实验表明机器人具有较高的鲁棒性,运动目标跟踪系统运行可靠。     

平行双目视觉系统的三维重建研究

随着图像处理,模式识别的快速发展,人们对双目视觉系统和三维创建越来越重视.本文研究和设计一套双目视觉系统目的是获得生动的立体图像.从二维图像恢复到三维图像实现了三维物体的可视化.     

一种改进的区域双目立体匹配方法

双目立体匹配是机器视觉中的热点、难点问题。分析了区域立体匹配方法的优缺点,提出了改进的区域立体匹配方法。首先,采集双目视觉图像对对图像对进行校正、去噪等处理,利用颜色特征进行图像分割,再用一种快速有效的块立体匹配算法对图像进行立体匹配。然后,在匹配过程中使用绝对误差累积(SAD)的小窗口来寻找左右两幅图像之间的匹配点。最后,通过滤波得到最终的视差图。实验表明:该方法能够有效地解决重复区域、低纹理区域、纹理相似区域、遮挡区域等带来的误匹配问题,能得到准确清晰的稠密视差图。     

Skeleton pruning as trade-off between skeleton simplicity and reconstruction error

The position and orientation of moving platform mainly depends on global positioning system and inertial navigation system in the field of low-altitude surveying, mapping and remote sensing and land-based mobile mapping system. However, GPS signal is unavailable in the application of deep space exploration and indoor robot control. In such circumstances, image-based methods are very important for self-position and orientation of moving platform. Therefore, this paper firstly introduces state of the art development of the image-based self-position and orientation method (ISPOM) for moving platform from the following aspects: 1) A comparison among major image-based methods (i.e., visual odometry, structure from motion, simultaneous localization and mapping) for position and orientation; 2) types of moving platform; 3) integration schemes of image sensor with other sensors; 4) calculation methodology and quantity of image sensors. Then, the paper proposes a new scheme of ISPOM for mobile robot — depending merely on image sensors. It takes the advantages of both monocular vision and stereo vision, and estimates the relative position and orientation of moving platform with high precision and high frequency. In a word, ISPOM will gradually speed from research to application, as well as play a vital role in deep space exploration and indoor robot control.     

BETWEEN LOCATION AWARENESS AND AWARE LOCATIONS: WHERE TO PUT THE INTELLIGENCE

This article presents a review on vision-aided systems and proposes an approach for visual rehabilitation using stereo vision technology. The proposed system utilizes stereo vision, image processing methodology, and a sonification procedure to support blind mobilization. The developed system includes wearable computer, stereo cameras as vision sensor, and stereo earphones, all molded in a helmet. The image of the scene in front of the visually handicapped is captured by the vision sensors. The captured images are processed to enhance the important features in the scene in front for mobilization assistance. The image processing is designed as a model of human vision by identifying the obstacles and their depth information. The processed image is mapped onto musical stereo sound for the blind's understanding of the scene in front. The developed method has been tested in the indoor and outdoor environments and the proposed image processing methodology is found to be effective for object identification.     

An algorithm for the visualization of stereo images simultaneously captured with different exposures

The visualization of stereo images obtained from two eyepiece cameras of a stereo microscope with different exposures is studied. This problem is solved to improve the quality of resulting images in the case when one image is not sufficient for capturing an object with the desired color reproduction accuracy and high level of detail both in dark and light regions. An approach to solving this problem in which differently exposed images are split between two views is considered. This approach allows us to significantly reduce the capturing time and to enhance the quality of capturing moving objects. The algorithm described in [1] is used as the basic algorithm; the main steps of this algorithm are the stereo matching of two input images and the construction of high dynamic range images. Modifications of the basic algorithm that use different stereo matching techniques are proposed. The application of the algorithm described in [2] for the visualization of stereo images without constructing high dynamic range images is discussed. A database of images captured with different exposures by a stereo microscope is created. The quality of algorithms applied to the images from this database is evaluated in the HDR-VDP-2.2 metric [3].     

Epipolar geometry for prism-based single-lens stereovision

In order to simplify the design and implementation of a stereo vision system, prism has been used to capture stereo images with a single camera. This kind of system not only provides advantages over traditional two-camera stereo, but also reduces the complexity and cost of acquiring stereoscopic image. This paper investigated the characteristics of epipolar geometry for a single-lens prism-based stereovision. The prism was considered as a single optical lens. By analyzing each plane individually and then combining them together, an affine transformation matrix which can express the relationship between an object point and its image was derived. Then, the homography between object point and its image was established. Finally, the epipolar geometry as well as the epipolar rectification method was proposed. Experimental results verify that rectification of the image pair based on our proposed model can achieve better performance with much less geometric distortion.     

一种基于颜色信息的足球机器人目标搜索方法

针对实际比赛中足球机器人视觉系统不能快速、准确地搜索到目标物体的问题,分析了RGB空间模型的优缺点以及基于彩色HSI变换原理,结合足球机器人的实际情况采用了一种从RGB空间到HIS空间快速变换的方法对颜色信息进行处理.同时,通过分析以往的目标搜索方法的优缺点,提出了一种基于颜色索引表的顺序网格法和种子填充法相结合的目标搜索方法,并在足球机器人视觉系统中进行了实验.实验结果表明这种方法既在一定的程度上降低了噪声干扰的影响,又避免了逐个像素计算颜色值,大大降低了计算量,从而提高了系统的实时性和可靠性.