Description: 用vc++6.0进行开发.主要包括了图像处理的一些方法.和视频图像的帧间差分法,三帧差分法,主要处理单目标和双目标.并对目标的位置进行标定-used for the development. Including the main image processing methods. Video image frames difference France, three difference method, which mainly deals with the single goal and two goals. as well as the position calibration Platform: |
Size: 136820 |
Author:蝈蝈 |
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Description: 用vc++6.0进行开发.主要包括了图像处理的一些方法.和视频图像的帧间差分法,三帧差分法,主要处理单目标和双目标.并对目标的位置进行标定-used for the development. Including the main image processing methods. Video image frames difference France, three difference method, which mainly deals with the single goal and two goals. as well as the position calibration Platform: |
Size: 136192 |
Author:蝈蝈 |
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Description: 摄像头标定的代码,OPENCV没有提供完整的示例,自己整理了一下,贴出来记录。利用cvFindChessboardCorners找到棋盘在摄像头中的2D位置,
再用cvCalibrateCamera2计算内参,
最后用cvUndistort2纠正图像的变形。
-Camera calibration code, OPENCV did not provide a complete example of its own collation, then paste it records. The use of chessboard cvFindChessboardCorners found in the 2D camera position, and then calculating the internal cvCalibrateCamera2, and finally used to correct image distortion cvUndistort2. Platform: |
Size: 15360 |
Author:马连洋 |
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Description: 基于atmel avr mega8和gcc编译器的读flash固定位置的时钟校准字节的程序。-Atmel avr mega8 and based on the gcc compiler for fixed position reading of flash byte clock calibration procedures. Platform: |
Size: 8192 |
Author:张洁 |
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Description: 摄像机标定:确定摄像机位置,属性参数和建立成像模型,以确定空间坐标系中物体点同它在图像平面上象点之间的对应关系。包括确定摄像机内部几何和光学特性(内部参数)和确定摄像机在一个世界坐标系中的三维位置和方向(外部参数)。-Camera Calibration: To determine the camera position, attributes the establishment of imaging model parameters and to determine the spatial coordinates of objects in points with it in the image plane as point correspondence between. Including the identification of the internal camera geometric and optical characteristics (internal parameters) and identify video cameras in a world coordinate system in three-dimensional position and orientation (external parameters). Platform: |
Size: 666624 |
Author:hexiang |
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Description: 基于多传感器的自治潜水器定位和创建地图方法
摘要:利用传感器间的外标定方法,把成像声纳的特征元素转换到相机坐标系中,再利用计算机视觉领域的struction fron motion 方法进行求解。-Multi-sensor based on the autonomy of underwater vehicle position and the creation of the map method Abstract: The use of outside inter-sensor calibration method, the characteristics of the sonar imaging element to the camera coordinate system conversion, the re-use the field of computer vision methods struction fron motion to solve. Platform: |
Size: 48128 |
Author:shuoshuo |
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Description: 使用激光进行多摄像机的定标,用于Linux系统。
MATLAB算法。可以对标定视频里的激光点位置。-The use of laser multi-camera calibration, for Linux. MATLAB algorithm. Can calibrate the laser point position in the video. Platform: |
Size: 16727040 |
Author:蚂蚁 |
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Description: Camera calibration consists in the estimation of a model for an un-calibrated camera. The objective is to find the external parameters (position and orientation relatively to a world co-ordinate system), and the internal parameters of the camera (principal point or image centre, focal length and distortion coefficients). One of the most used camera calibration techniques is the one proposed by Tsai Platform: |
Size: 1192960 |
Author:Ahmed |
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Description: 首先自制一张标定图片,用A4纸打印出来,设定距离,再设定标定棋盘的格子数目,如8×6,然后利用cvFindChessboardCorners找到棋盘在摄像头中的2D位置,这里cvFindChessboardCorners不太稳定,有时不能工作,也许需要图像增强处理。
计算实际的距离,应该是3D的距离。我设定为21.6毫米,既在A4纸上为两厘米。
再用cvCalibrateCamera2计算内参,
最后用cvUndistort2纠正图像的变形。
-First, a self-calibration picture, with A4 paper, print it out, set the distance, then set the calibration number of the board of the lattice, such as 8 × 6, and then use cvFindChessboardCorners find the board in the position of the camera in 2D, where cvFindChessboardCorners less stable, sometimes does not work, may need to image enhancement. Calculate the actual distance, the distance should be 3D. I set 21.6 mm, both in the A4 paper to two centimeters. Then cvCalibrateCamera2 calculated internal reference, and finally with cvUndistort2 correct the distortion. Platform: |
Size: 8192 |
Author:高东旭 |
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Description: GPS方位标定与目标遥测系统 XW-ADU3603
用户手册,专门配合激光测距机使用-GPS telemetry system with the target calibration position XW-ADU3603 user manual, specifically with the use of laser range finder Platform: |
Size: 1055744 |
Author:ZSR |
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Description: 干涉参数定标对于机载双天线InSAR(Interferometric Synthetic Aperture Radar)系统的大面积高精度数字高程模型(DEM,Digital Elevation Model)获取具有重要意义。为了高效地进行干涉参数定标,本文从双天线InSAR获取DEM的基本原理出发,构建了一种新的考虑干涉相位偏置、基线长度和基线水平角三个干涉参数的外定标模型,设计了外定标模型的未知参数解算方案。利用GPS(Global Position System,全球定位系统)实测的高程控制点对中国科学院电子学研究所自主研制的机载双天线InSAR系统进行了干涉参数定标实验,统计了利用定标后干涉参数反演地面高程的精度,验证了所采用外定标模型及解算方案的正确性和有效性。-It is significant to calibrate interferometric parameters of dual-antenna airborne InSAR(Interferometric Synthetic Aperture Radar)systems for deriving accurate DEM (Digital Elevation Model) with large areas. A new outside calibration model considering phase offset, baseline length and baseline angle was proposed in order to calibrate interferometric parameters effectively, which was induced from the basic theory of DEM deriving from InSAR. And its solution scheme was designed. The outside calibration experiments were done with height control points measured by GPS to calibrate the dual-antenna airborne InSAR system researched independently by Institute of Electronics, Chinese Academy of Sciences. The accuracy of heights derived with calibrated interferometric parameters was calculated, as validated the proposed calibration model and its solution algorithm. Platform: |
Size: 1343488 |
Author:jgw |
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Description: 基于机器视觉,控制三自由度运动控制台来调整显微镜位置,通过图像处理得到易拉罐的表面刻痕大小和长度。-The software control the motion platform with 3 d.o.f. to position the microscope and then test the notch of cans using image processing. Platform: |
Size: 6623232 |
Author:郑慧峰 |
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Description: 解决人脸识别系统中,人脸图像的尺寸归一化、位置校准、光照补偿、直方图均衡化、特征提取的工作-Solve the face recognition system, the size of the face image normalization, position calibration, illumination compensation, histogram equalization, feature extraction work Platform: |
Size: 4096 |
Author:瑜Orz |
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Description: FOG双轴旋转六位置现场标定方法。针对FOG,利用双轴旋转,有效提高标定精度,降低对转台精度的要求-FOG two- axis rotating six- position field calibration method. According to the FOG, the two axis rotation is used to effectively improve the calibration accuracy and reduce the accuracy of the turntable. Platform: |
Size: 338944 |
Author:杨磊 |
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Description: 介绍一下制作这个类库的流程:新建一个项目→选择 类库 → 在这个类库的基础上添加新建项 → 用户控件→添加 引用HalconDotNet → 拖一个 Halcon显示图像的HalconWindow 上去 → 改写,添加 放大 缩小的功能 完毕。(Description: halcon and C # joint programming, control function 1, support the mouse button zoom and left drag 2, support in the image after scaling, region, xld, roi can reproduce 3, support region, xld in accordance with the specified color display, and In the zoom after the recurrence of 4, support rectangle 1, rectangle 2, circle, and straight roi drawing 5, you can display the current position of the left mouse button image gray value 6, you can save the original image, or screenshots of the current window
(Halcon and C # joint programming)) Platform: |
Size: 371712 |
Author:ms_mm
|
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Description: 给定测量的位置值和角度,对机器人D-H参数标定(Given the position and angle of the measurement, the robot D-H parameters are calibrated) Platform: |
Size: 38912 |
Author:巙钺
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Description: 这是一篇关于VI-SLAM的优秀学位论文
VI-SLAM (Visual-Inertial Simultaneous Localization and Mapping) is a popular way for
robotics navigation and tracking. With the help of sensor fusion from IMU and camera, VI-SLAM
can give a more accurate solution for navigation. One important problem needs to be solved in
VI-SLAM is that we need to know accurate relative position between camera and IMU, we call
it extrinsic parameter. However, our measurement to the rotation and translation between IMU
and camera is noisy. If the measurement is slightly o, the result of SLAM system will be much
more away from the ground truth after a long run. Optimization is necessary. This paper uses
a global optimization method called Bayesian Optimization to optimize the relative pose between
IMU and camera based on the sliding window residual output from VISLAM. The advantage of
using Bayesian Optimization is that we can get an accurate pose estimation between IMU and
camera from a large searching range. Whats more, thanks to the Gaussian Process or T process
of Bayesian Optimization, we can get a result with a known uncertainty, which cannot be done by
many optimization solutions. Platform: |
Size: 3178620 |
Author:kcfucx |
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