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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
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Size: 12192309 |
Author: kankan |
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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
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Size: 12191744 |
Author: kankan |
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Description: 霍夫变换和RANSAC... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
-observe that Hough transform and RANSAC can estimate line
parameters even with outliers.
Write a program to estimate the parameters of a 2D circle.
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Size: 1024 |
Author: zhengyan |
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Description: 这是一个印度人编的程序，用于两图像单应矩阵和变换结果的求取-This function estimates 2D-2D plane projective homography between two perspective images using Direct Linear Transformation, RANSAC and Levenberg Marquardt optimisation.
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Size: 29696 |
Author: 苏营 |
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Description: RANSACFITHOMOGRAPHY - fits 2D homography using RANSAC-RANSACFITHOMOGRAPHY- fits 2D homography using RANSAC
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Size: 2048 |
Author: yue hou |
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Description: 图像中用到的RANSAC算法包。RANSAC Toolbox by Marco Zuliani-this is a research (and didactic) oriented toolbox to explore the
RANSAC algorithm. The functions are reasonably well documented and
there is a directory containing examples to estimate 2D lines, 3D
planes, RST transformations and homographies in presence of
outliers. However a previous exposure to the algorithm may be very
helpful in understanding the options available. A tutorial introducing
RANSAC with several examples using this toolbox can be found in the
documentation directory.
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Size: 2593792 |
Author: |
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Description: raft
This chapter introduces the problem of parameter estimation when the measurements
arecontaminated by outliers. To motivate the results that will be presented in the
next chapters and to understand the power of RANSAC, we will study a simple
problem: tting a 2D line to a set of points on the plane. Despite its simplicity,
this problem retains all the challenges that are encountered when the models used
to explain the measurements are more complex.-
This chapter introduces the problem of parameter estimation when the measurements
arecontaminated by outliers. To motivate the results that will be presented in the
next chapters and to understand the power of RANSAC, we will study a simple
problem: tting a 2D line to a set of points on the plane. Despite its simplicity,
this problem retains all the challenges that are encountered when the models used
to explain the measurements are more complex.
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Size: 1244160 |
Author: 杨尚波 |
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Description: 用matlab实现的有关Ransac算法做的2D及3D拟合效果。-Use the matlab achieve Ransac of algorithm do 2D and 3D fitting effect.
Platform: |
Size: 113664 |
Author: wangbinbin |
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