Description: The problem of image registration subsumes a number of problems and techniques in multiframe
image analysis, including the computation of optic flow (general pixel-based motion), stereo
correspondence, structure from motion, and feature tracking. We present a new registration
algorithm based on spline representations of the displacement field which can be specialized to
solve all of the above mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of
the above problems. Using a spline-based description of the flow removes the need for overlapping
correlation windows, and produces an explicit measure of the correlation between adjacent flow
estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D
projective scene geometry. We also provide results on a number of standard motion sequences. Platform: |
Size: 486459 |
Author:刘长乐 |
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Description: 深入浅出介绍计算机视觉的最新动态。内容包括：
* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration
* Extracting camera motion and scene structure from image sequences
* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms
* Image-based lighting for illuminating scenes and objects with real-world light images
* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more
* Face detection, alignment, and recognition--with new solutions for key challenges
* Perceptual interfaces for integrating vision, speech, and haptic modalities
* Development with the Open Source Computer Vision Library (OpenCV)
* The new SAI framework and patterns for architecting computer vision applications Platform: |
Size: 12192309 |
Author:kankan |
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Description: The problem of image registration subsumes a number of problems and techniques in multiframe
image analysis, including the computation of optic flow (general pixel-based motion), stereo
correspondence, structure from motion, and feature tracking. We present a new registration
algorithm based on spline representations of the displacement field which can be specialized to
solve all of the above mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of
the above problems. Using a spline-based description of the flow removes the need for overlapping
correlation windows, and produces an explicit measure of the correlation between adjacent flow
estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D
projective scene geometry. We also provide results on a number of standard motion sequences. Platform: |
Size: 486400 |
Author:刘长乐 |
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Description: 深入浅出介绍计算机视觉的最新动态。内容包括：
* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration
* Extracting camera motion and scene structure from image sequences
* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms
* Image-based lighting for illuminating scenes and objects with real-world light images
* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more
* Face detection, alignment, and recognition--with new solutions for key challenges
* Perceptual interfaces for integrating vision, speech, and haptic modalities
* Development with the Open Source Computer Vision Library (OpenCV)
* The new SAI framework and patterns for architecting computer vision applications-Easy to introduce the latest developments in computer vision. Include:* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration* Extracting camera motion and scene structure from image sequences* Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms* Image-based lighting for illuminating scenes and objects with real-world light images* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more* Face detection, alignment, and recognition- with new solutions for key challenges* Perceptual interfaces for integrating vision, speech, and haptic modalities* Development with the Open Source Computer Vision Library (OpenCV)* The new SAI framework and patterns for architecting computer vision applications Platform: |
Size: 12191744 |
Author:kankan |
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Description: Recovering 3-D structure from motion in noisy 2-D images is a problem addressed by many vision system researchers. By consistently tracking feature points of interest across multiple images using a methodology first described by Lucas-Kanade, a 3-D shape of the scene can be reconstructed using these features points using the factorization method developed by Tomasi-Kanade. Platform: |
Size: 4657152 |
Author:Stephen Bishop |
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Description: sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points. Platform: |
Size: 393216 |
Author:picab |
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Description: Bundler is a structure-from-motion system for unordered image
collections (for instance, images from the Internet). Bundler takes a
set of images, image features, and image matches as input, and
produces a 3D reconstruction of the camera and (sparse) scene geometry
as output. The system, described in [1] and [2], reconstructs the
scene incrementally, a few images at a time, using a modified version
of the Sparse Bundle Adjustment package of Lourakis and Argyros [3] as
the underlying optimization engine.
Currently, Bundler has been primarily compiled and tested under Linux
(though a Windows version for cygwin has also been released). Platform: |
Size: 5941248 |
Author:陳奕均 |
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Description: 刚性位置变化计算，输入物体在空间坐标系中的坐标，以及旋转向量和平移向量，计算其在摄像机坐标系中的坐标。- [Y,dYdom,dYdT] = rigid_motion(X,om,T)
Computes the rigid motion transformation Y = R*X+T, where R = rodrigues(om).
INPUT: X: 3D structure in the world coordinate frame (3xN matrix for N points)
(om,T): Rigid motion parameters between world coordinate frame and camera reference frame
om: rotation vector (3x1 vector) T: translation vector (3x1 vector)
OUTPUT: Y: 3D coordinates of the structure points in the camera reference frame (3xN matrix for N points)
dYdom: Derivative of Y with respect to om ((3N)x3 matrix)
dYdT: Derivative of Y with respect to T ((3N)x3 matrix)
Definitions:
Let P be a point in 3D of coordinates X in the world reference frame (stored in the matrix X)
The coordinate vector of P in the camera reference frame is: Y = R*X+ T
where R is the rotation matrix corresponding to the rotation vector om: R = rodrigues(om)
Important function called within that program:
rodrigues.m: Computes the Platform: |
Size: 1024 |
Author:shuang |
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Description: 集束调整是指同时调整相机参数和物点坐标，使重投影误差取得最小值的优化过程，可用于三维重建-sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points. Platform: |
Size: 524288 |
Author:liulihong |
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Description: Bundler是一个采用C和C++开发的称为sfm（struct-from-motion）的系统，它能够利用无序的图片集合（例如来自网络的图片）重建出3D的模型。最早的版本被用在Photo Tourism的项目上。
Bundler的输入是一些图像、图像特征以及图像匹配信息，输出则是一个根据这些图像反应的场景的3D重建模型，伴有少量识别得到的相机以及场景几何信息。系统借用一个由Lourakis 和Argyros提供的称为Sparse Bundle Adjustment的开发包的修改版，一点一点递增地重建出图像场景。Bundler已经成功的应用在许多网络相册系统，尤其是一些建筑相册里。
-Bundler is a structure-from-motion (SfM) system for unordered image collections (for instance, images from the Internet) written in C and C++. An earlier version of this SfM system was used in the Photo Tourism project.
Bundler takes a set of images, image features, and image matches as input, and produces a 3D reconstruction of camera and (sparse) scene geometry as output. The system reconstructs the scene incrementally, a few images at a time, using a modified version of the Sparse Bundle Adjustment package of Lourakis and Argyros as the underlying optimization engine. Bundler has been successfully run on many Internet photo collections, as well as more structured collections.
Platform: |
Size: 5009408 |
Author:zero |
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Description: 通过labview实现在solidwork下对3D运动你结构的仿真，旋转及直线运动的实现。-Labview achieved by 3D movement in solidwork under the structure of your simulation, rotary and linear motion to achieve. Platform: |
Size: 7747584 |
Author:蔡文兵 |
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Description: 图像处理 o 梯度 边缘和角点 o 采样 差值和几何变换 o 形态学操作 o 滤波和彩色变换 o 金字塔及其应用 o 连接组件 o 图像和轮廓矩 o 特殊图像变换 o 直方图 o 匹配 结构分析 o 轮廓处理 o 计算几何 o 平面划分 运动分析和对象跟踪 o 背景统计量的累积 o 运动模板 o 对象跟踪 o 光流 o 预估器 模式识别 o 目标检测 照相机定标和三维重建 o 照相机定标 o 姿态估计 o 极线几何 函数列表 参考图像处理注意:本章描述图像处理和分析的一些函数-O gradient edge and corner of the image processing o Sampling difference and geometric transformations o filtering and color transform morphological operations o o pyramid and its application o connected components o image and contour moments o special image transformation o Histogram o matching structure analysis o contour processing o computational geometry o the plane divided motion analysis and object tracking cumulative o Motion templates o o background statistics object tracking o optical flow o predictor pattern recognition o target detection camera calibration and 3D reconstruction o camera calibration o attitude estimates o epipolar geometry function list reference image processing Note: This chapter describes the image processing and analysis functions Platform: |
Size: 9968640 |
Author:diaoguangqiang |
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Description: opencv最新书籍《Master OpenCV with Practical Computer Vision Projects》。基于opencv2.4.3编写。采用了实例工程方式讲解。-opencv book:
Chapters:
Ch1) Cartoonifier and Skin Changer for Android, by Shervin Emami.
Ch2) Marker-based Augmented Reality on iPhone or iPad, by Khvedchenia Ievgen.
Ch3) Marker-less Augmented Reality, by Khvedchenia Ievgen.
Ch4) Exploring Structure from Motion using OpenCV, by Roy Shilkrot.
Ch5) Number Plate Recognition using SVM and Neural Networks, by David Escrivá.
Ch6) Non-rigid Face Tracking, by Jason Saragih.
Ch7) 3D Head Pose Estimation using AAM and POSIT, by Daniel Lélis Baggio.
Ch8) Face Recognition using Eigenfaces or Fisherfaces, by Shervin Emami.
Ch9) Developing Fluid Wall using the Microsoft Kinect, by Naureen Mahmood.
Platform: |
Size: 6326272 |
Author:王邦平 |
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Description: Use affine structure from motion to compute 3D location and orientation + camera locations [RANSAC]
-Use affine structure from motion to compute 3D location and orientation + camera locations [RANSAC]
Platform: |
Size: 25192448 |
Author:Sam |
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Description: This paper aims to present a new method for generating incoherent seismic ground
motions on the basis of the stochastic deconvolution technique and the spectral representation
method. The generated free field motion satisfies the imposed statistical properties on the free
surface and is composed of elementary plane waves of types SH, P-SV incoming from all directions. This will allow 3D soil-structure interaction analyses to be performed with spatially
varying seismic motions in the case of structure with embedded foundation. Eventually, structural non-linearity can be accounted for when the SSI analysis is performed in the time domain. Platform: |
Size: 323584 |
Author:Aleja28 |
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Description: 目前，OpenCV逐步成为一个通用的基础研究和产品开发平台。本书是国内第一本全面介绍OpenCV的中文版图书，对OpenCV开放源代码计算机视觉库进行了详细讲解。OpenCV由一系列C函数和C++类构成，功能涵盖图像处理、计算机视觉和模式识别等领域。OpenCV实现了大量通用算法，涉及到图像处理、结构分析、运动检测、摄像机定标、三维重建以及机器学习等方面，并有较高的运行效率。书中所有实例均提供了C／C++语言的源代码。本书附光盘1张，内容包括OpenCV 1.0分别在windows和Linux下的安装程序，以及书中所有实例的源代码-Currently, OpenCV gradually become a common platform for basic research and product development. This book is the first comprehensive introduction to the Chinese version of the book OpenCV for computer vision library OpenCV open source were explained in detail. OpenCV by a series of C functions and C++ class structure, functions cover image processing, computer vision and pattern recognition. OpenCV to achieve a lot of common algorithms, related to image processing, structural analysis, motion detection, camera calibration, 3D reconstruction, and machine learning, etc., and have a higher operating efficiency. The book is available in all instances of C/C++ language source code. A book with CD-ROM, including OpenCV 1.0 respectively installer in windows and Linux, as well as the source code for all instances in the book Platform: |
Size: 23344128 |
Author:wulicheng |
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Description: 这是一个基于openGl制作的一个手势识别程序(This is a 3D hand model developed mainly for vision-based hand motion analysis. The hand model is modeled as a set of rigid quadratic surfaces, and has 27 degrees-of-freedom (DoFs) including 6 DoFs of global motion and 21 DoFs of local motion. The hand skeleton is modeled as a kinematic chain of 20 joints connected by bones in a tree structure with the root at the wrist. In this program you can view the model from different positions and perspectives, and manipulate each DoF separately. More importantly, to assist research in this area, we also provide functions to generate the depth image, silhouette image and edge images, which can be easily used for model-based matching between the input and the 3D hand model.) Platform: |
Size: 71599104 |
Author:HUST——lxl
|
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Description: 3D点云重建 3D点云重建Berkeley SfM is a structure from motion library created to explore new solutions to challenging 3D reconstruction problems (large scale, indoors, incremental, homogeneously textured, etc.). It is developed by(Structrue From Motion for Education Purpose
Version 2 @ 2014
Written by Jianxiong Xiao (MIT License)
This code demonstrates how a traditional structure from motion pipeline is done and how to compute a dense point cloud by matching propagation in a simplest way. It is mainly designed for teaching a computer vision lecture at Princeton. Please check the slides and the homework assignment together with this code release. Although it is for education purpose, it is implemented in a nice way that it actually works for real photos. It is just probably quite slow compared to more optimized system, such as Bundler from Noah Snavely.
Usage: run SFMedu2.m in Matlab.
Acknowledgement: Thanks for Fisher Yu for bug fixing and feedback. We also thanks many people for making their functions publicly available online. Note that the third party library may have different licenses that you need to follow. We include them for the convenience for the users and don't imply any copyright issues.) Platform: |
Size: 10240 |
Author:fangyz |
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Search - 3D motion structure