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the6thchapter
- 基于OpneCV的计算机视觉技术实现光盘,第六章的内容。- computer vision technology realziation based on OpenCV disk, the sixth chapter
Feature-detection-(computer-vision)---Wikipedia--
- feature detection methods from wikipedia
OpenCV-VIDEO-DETCTION
- 计算机视觉是研究用计算机模拟生物外显或宏观视觉功能的科学和技术。作 为计算机视觉研究的一个分支—运动目标的检测与跟踪,就是对视场内的运动目 标,如人或车辆等,进行实时的观测,并在此基础上对被观测对象进行分类,然 后分析它们的行为。近年来,计算机视觉的研究重点已经从对静态图像的研究过 渡到对动态图像序列的研究上面,这方面的典型应用包括自动化的视频监控系 统、视频MPEG编解码技术、人机交互的感知接口、军事上的制导、雷达视频 图像中的
segment
- Segment may mean: The divisions found in the internal section of a citrus fruit Market segment, the smaller subgroups comprising a market Computing Segmentation (memory), the division of computer memory into segments Image segment c
DIP--vc_matlab
- 计算机视觉和图像处理的基于VC和matlab的源码-Computer vision and image processing based on VC and Matlab source code
eigface
- Eigenfaces are a set of eigenvectors used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby (1987) and used by Matthew Turk and Alex Pentland in face classif
blepo_0.6.8
- Blepo计算机视觉库 Blepo是一个开放源代码的C / C + +库的,便于计算机视觉的研究和教育。它的目标是三个方面: 使研究人员能够专注于算法的开发,而不是低层次的细节,比如内存管理,读/写文件,拍摄图像,可视化, 在不牺牲效率 在C + +环境下,很容易使用,使教育工作者和学生学习图像处理 捕捉到一个比较成熟的,完善的算法库,使他们的社会既没有被别人使用,以避免推倒重来。-Blepo Computer Vision Library Blepo is an
em
- 在统计计算中,最大期望(EM)算法是在概率(probabilistic)模型中寻找参数最大似然估计或者最大后验估计的算法,其中概率模型依赖于无法观测的隐藏变量(Latent Variable)。最大期望经常用在机器学习和计算机视觉的数据聚类(Data Clustering)领域。 -In the statistical calculations, the maximum expected (EM) algorithm parameter maximum likelihood estimate
testehist
- computer vision histogram
Grimson-method
- the grimson method is a computer vision program that take a film and define movement in it.it is use full for process films from public pplaces camera.
Grims
- the grimson method is a computer vision program that take a film and define movement in it.it is use full for process films from public pplaces camera.
harandi_cvpr_2011_matlab
- 2012 ECCV 稀疏编码和 字典学习- Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach. European Conference on Computer Vision (ECCV), pp. 216-229, 2012.
09_Image_Filtering_Edge_Detection_09.pdf
- Computer Vision Note on Image Filtering
the8thchapter
- 基于OpneCV的计算机视觉技术实现光盘,第8章的内容。-CD-ROM based OpneCV computer vision technology, the contents of Chapter VI.
Robust-Image-Matching
- 图像匹配是计算机视觉中的最重要的任务之一。部分遮挡下的稳健的影像匹配空间变光照变化-Image matching is one of the most important tasks in computer vision. Robust Image Matching space under partial occlusion changing illumination change
AGAST-corner-detector
- 多尺度快速角点检测算法(FAST).Adaptive and generic corner detection based on the accelerated segment test. Computer Vision–ECCV 2010-Multi-scale fast corner detection algorithm (FAST) Adaptive and generic corner detection based on the accelerated segment test
Algorithms-and-Applications
- Computer Vision:Algorithms and Applications,Richard Szeliski,适合图像处理人群-Computer Vision: Algorithms and Applications, Richard Szeliski, suitable for image processing crowd
cameral
- 将一个虚拟正方体投映到墙角上, 属于计算机视觉里的现实增强-A virtual cube projector into a corner in the computer vision augmented reality
opencv.rar
- 是一本介绍了 opencv教程使用里的各种源码 该资料中 包括了关于计算机视觉的数学方法,工具,代码等,A opencv tutorial uses the data source, including mathematical methods, computer vision tools, code
Ransac
- RANSAC为RANdom SAmple Consensus的缩写,它是根据一组包含异常数据的样本数据集,计算出数据的数学模型参数,得到有效样本数据的算法。它于1981年由Fischler和Bolles最先提出[1]。 RANSAC算法经常用于计算机视觉中。例如,在立体视觉领域中同时解决一对相机的匹配点问题及基本矩阵的计算。 RANSAC算法的基本假设是样本中包含正确数据(inliers,可以被模型描述的数据),也包含异常数据(Outliers,偏离正常范围很远、无法适应数学模型的数据)