计算机视觉算法与应用的一些测试数据集和源码站点

以下是computer vision:algorithm and application计算机视觉算法与应用这本书中附录里的关于计算机视觉的一些测试数据集和源码站点,我整理了下,加了点中文注解。
Computer Vision:
Algorithms and Applications
Richard Szeliski
在本书的最好附录中,我总结了一些对学生,教授和研究者有用的附加材料。这本书的网址/Book包含了更新的数据集和软件,请同样访问他。
C.1 数据集
一个关键就是用富有挑战和典型的数据集来测试你算法的可靠性。当有背景或者他人的结果是可行的,这种测试可能甚至包含更多的信息(和质量更好)。
经过这些年,大量的数据集已经被提出来用于测试和评估计算机视觉算法。许多这些数据集和软件被编入了计算机视觉的主页。一些更新的网址,像CVonline
(homepages.inf.ed.ac.uk/rbf/CVonline ), VisionBib.Com (datasets.visionbib/ ), and Computer Vision online (computervisiononline/ ), 有更多最新的数据集和软件。
下面,我列出了一些用的最多的数据集,我将它们让章节排列以便它们联系更紧密。
第二章:图像信息
CUReT: Columbia-Utrecht 反射率和纹理数据库Reflectance and Texture Database, lumbia.edu/CAVE/software/curet/  (Dana, van Ginneken, Nayar et al. 1999).
Middlebury Color Datasets:不同摄像机拍摄的图像,注册后用于研究不同的摄像机怎么改变域和彩registered color images taken by different cameras to study how they transform gamuts and colors, vision.middlebury.edu/color/data/ Chakrabarti, Scharstein, and Zickler 2009).
第三章:图像处理
Middlebury test datasets for evaluating MRF minimization/inference algorithms评估隐马尔科夫随机场最小化和推断算法,
vision.middlebury.edu/MRF/results/ (Szeliski, Zabih, Scharstein et al. 2008).
第四章:特征检测和匹配
Affine Covariant Features database(反射协变的特征数据集) for evaluating feature detector and descriptor matching quality and repeatability(评估特征检测和描述匹配的质量和定位精度),  ac.uk/~vgg/research/affine/
(Miko-lajczyk and Schmid 2005; Mikolajczyk, Tuytelaars, Schmid et al. 2005).
Database of matched image patches for learning (图像斑块匹配学习数据库)and feature descriptor evaluation(特征描述评估数据库),
cvlab.epfl.ch/~brown/patchdata/patchdata.html
(Winder and Brown 2007; Hua,Brown, and Winder 2007).
第五章;分割
Berkeley Segmentation Dataset(分割数据库) and Benchmark of 1000 images labeled by 30 humans,(30个人标记的1000副基准图像)along with an evaluation, s.berkeley.edu/Research/Projects/CS/vision/grouping/segbench/  (Martin, Fowlkes, Tal et al. 2001).
Weizmann segmentation evaluation database of 100 grayscale images with ground truth segmentations,
www.wisdom.weizmann.ac.il/~vision/Seg Evaluation DB/index.html
(Alpert, Galun, Basri et al. 2007).
第八章:稠密运动估计
The Middlebury optic flow evaluation(光流评估) Web site, vision.middlebury.edu/flow/data/
(Baker, Scharstein, Lewis et al. 2009).
The Human-Assisted Motion Annotation database,(人类辅助运动数据库)
people.csail.mit.edu/celiu/motionAnnotation/  (Liu, Freeman, Adelson et al. 2008)
第十章:计算机摄像学
High Dynamic Range radiance(辐射)maps, /Research/HDR/
(De-bevec and Malik 1997).
Alpha matting evaluation Web site, alphamatting/ (Rhemann, Rother, Wang
et al. 2009).
第十一章:Stereo correspondence立体对应
Middlebury Stereo Datasets and Evaluation, vision.middlebury.edu/stereo/  (Scharstein
and Szeliski 2002).
Stereo Classification(立体分类) and Performance Evaluation(性能评估) of different aggregation(聚类) costs for stereo matching(立体匹配), www.vision.deis.unibo.it/spe/SPEHome.aspx  (Tombari, Mat-
toccia, Di Stefano et al. 2008).
Middlebury Multi-View Stereo Datasets,
vision.middlebury.edu/mview/data/  (Seitz,Curless, Diebel et al. 2006).
Multi-view and Oxford Colleges building reconstructions,
ac.uk/~vgg/data/data-mview.html .
Multi-View Stereo Datasets, cvlab.epfl.ch/data/strechamvs/  (Strecha, Fransens,
and Van Gool 2006).
Multi-View Evaluation,  cvlab.epfl.ch/~strecha/multiview/ (Strecha, von Hansen,
Van Gool et al. 2008).
第十二章:3D重建
HumanEva: synchronized video(同步视频) and motion capture (动作捕捉)dataset for evaluation of articulated human motion, vision.cs.brown.edu/humaneva/  Sigal, Balan, and Black 2010).
第十三章:图像渲染
The (New) Stanford Light Field Archive, lightfield.stanford.edu/ 
(Wilburn, Joshi,Vaish et al. 2005).
Virtual Viewpoint Video: multi-viewpoint video with per-frame depth maps,
research.microsoft/en-us/um/redmond/groups/ivm/vvv/  (Zitnick, Kang, Uytten-
daele et al. 2004).
第十四章:识别
查一系列的视觉识别数据库,在表14.1–14.2.除了那些,这里还有:
Buffy pose classes, ac.uk/~vgg/data/  buffy pose classes/ and Buffy
stickmen V2.1, ac.uk/~vgg/data/stickmen/index.html  (Ferrari,Marin-
pnp网络摄像机Jimenez, and Zisserman 2009; Eichner and Ferrari 2009).
H3D database of pose/joint annotated photographs of humans,
s.berkeley.edu/~lbourdev/h3d/  (Bourdev and Malik 2009).
Action Recognition Datasets, www.cs.berkeley.edu/projects/vision/action, has point-
ers to several datasets for action and activity recognition, as well as some papers.(有一些关于人活动和运动的数据库和论文) The human action database at www.nada.kt
h.se/cvap/actions/  包含更多的行动序列。

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