常用图像数据库

爱被打了一巴掌 2022-07-27 17:28 222阅读 0赞

1， [http://www.multitel.be/cantata/][http_www.multitel.be_cantata]

这个网址提供了大量的视频和图像的数据库下载索引，并有相应的介绍，强烈推荐！大家慢慢去找寻自己的惊喜吧

2， [http://www.cvpapers.com/datasets.html][http_www.cvpapers.com_datasets.html]

CVDatasets on the web ， 主要好像是直立行人检测....

3， [http://www.cvc.uab.es/adas/site/?q=node/7][http_www.cvc.uab.es_adas_site_q_node_7]

里面又有好几种数据库可以下载：CVC Virtual Pedestrian Dataset、CVC-01Pedestrian Dataset、CVC-02 PedestrianDataset

4， [http://www.cis.upenn.edu/~jshi/ped\_html/][http_www.cis.upenn.edu_jshi_ped_html]

Databasedescription：This is an image database containing images that are usedfor pedestrian detection in the experiments reported in [\[1\]][1]. The images are taken from scenes around campus

and urban street. Theobjects we are interested in these images are pedestrians. Each image will haveat least one pedestrian in it.

Theheights of labeled pedestrians in this database fall into \[180,390\] pixels. Alllabeled pedestrians are straight up.

Thereare 170 images with 345 labeled pedestrians, among which 96 images are takenfrom around University of Pennsylvania, and other 74 are taken from aroundFudan University.

5， [http://www.vision.caltech.edu/Image\_Datasets/CaltechPedestrians/][http_www.vision.caltech.edu_Image_Datasets_CaltechPedestrians]

Caltech Pedestrian Detection Benchmark：The Caltech Pedestrian Dataset consists of approximately10 hours of 640x480 30Hz video taken from a vehicle

driving through regulartraffic in an urban environment. About 250,000 frames (in 137 approximatelyminute long segments) with a total of 350,000 bounding boxes and 2300 uniquepedestrians were annotated. The annotation includes temporal correspondencebetween

bounding boxes and detailed occlusion labels. More information can befound in our

[PAMI2011][] and

[CVPR2009][] benchmarking papers.

6， [http://www.edgar-seemann.de/pd/datasets.py][http_www.edgar-seemann.de_pd_datasets.py]

PedestrianDetection

7， [http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html\#Database][http_www.wisdom.weizmann.ac.il_vision_SpaceTimeActions.html_Database]

Weizmann 人体行为库

[http://www.nada.kth.se/cvap/actions/][http_www.nada.kth.se_cvap_actions]

KTH人体行为数据库

[http://4drepository.inrialpes.fr/public/viewgroup/6][http_4drepository.inrialpes.fr_public_viewgroup_6] INRIA XMAX多视角视频库

[http://vision.eecs.ucf.edu/data.][http_vision.eecs.ucf.edu_data.] [html][http_vision.eecs.ucf.edu_data.]

UCF Sports 数据库

[http://www.di.ens.fr/~laptev/actions/hollywood2][http_www.di.ens.fr_laptev_actions_hollywood2] [/][http_www.di.ens.fr_laptev_actions_hollywood2]

Hollywood 人体行为库

[http://vision.stanford.edu/Datasets/OlympicSports/][http_vision.stanford.edu_Datasets_OlympicSports]

Olympic sports dataset

这几个数据库均是基于动作/行为识别的(在第1条网址中也可以找到它们的下载地址)，文章《视频中行为识别公开数据库汇总

》对它们的评价比较中肯，可以参看： [http://blog.sina.com.cn/s/blog\_631a4cc40101138j.html][http_blog.sina.com.cn_s_blog_631a4cc40101138j.html]

8， [http://homepages.inf.ed.ac.uk/rbf/BEHAVE/][http_homepages.inf.ed.ac.uk_rbf_BEHAVE]

Computer-assistedprescreening of video streams for unusual activities

9， [http://www.cc.gatech.edu/cpl/projects/monsoon/PropagationNet/PropagationNet.htm][http_www.cc.gatech.edu_cpl_projects_monsoon_PropagationNet_PropagationNet.htm]

Propagation Networks for Recognizing Partially OrderedSequential Activity. Goals：

Represent and fuse human knowledge of daily activities with noisy perceptual features

Detect and recognize an activity

Pinpoint components of the activity and detect missing or improperly performed steps

10， [http://root.simpleinfo.net/1984DA173065/AreaDatum.aspx][http_root.simpleinfo.net_1984DA173065_AreaDatum.aspx]

由模式识别国家重点实验室提供的链接，数据量比较大，通常需要签属协议，以光盘形式拿到数据。可以下载的有 [虹膜库数据][Link 1]、 [掌纹数据库][Link 2]、 [步态数据库][Link 3]、 [中文语言资源库][Link 4]、 [笔迹数据库][Link 5]、 [三维人脸数据库][Link 6]、 [行为分析数据库][Link 7]

11， [http://www.datatang.com][http_www.datatang.com]

这里也提供一些数据库下载，种类比较多，但是需要付费，不是打广告哦，呵呵，建议大家可以从它那里的数据库介绍中找些线索来进行google，然后你就有可能下载到原始且免费的了哦

12，http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/

MATLAB and Octave Functions for Computer Vision and Image Processing

13，http://mocap.cs.cmu.edu/

CMU Graphics Lab Motion Capture Database

14，http://www.cs.cmu.edu/~cil/v-images.html

Computer Vision Test Images

15，http://getalp.imag.fr/xwiki/bin/view/HISData/

http://www.springerlink.com/content/u57j444p0537p40t/

Health Smart Home (HIS) datasets 从文章作者那里要来的链接

16，http://architecture.mit.edu/house\_n/data/

与15的一样，是关于智能家居、老人看护类的日常生活行为

1. Weizmann 人体行为库

此数据库一共包括90段视频，这些视频分别是由9个人执行了10个不同的动作（bend,

jack, jump, pjump, run, side, skip, walk, wave1,wave2）。视频的背景，视角以及摄像头都是静止的。而且该数据库提供标注好的前景轮廓视频。不过此数据库的正确率已经达到100%了，现在发文章基本没人用了呀。下载地址： [http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html][http_www.wisdom.weizmann.ac.il_vision_SpaceTimeActions.html]

2. KTH人体行为数据库

该数据库包括6类行为（walking, jogging, running, boxing, hand waving, hand clapping）,是由25个不同的人执行的，分别在四个场景下，一共有599段视频。背景相对静止，除了镜头的拉近拉远，摄像机的运动比较轻微。这个数据库是现在的benchmark，正确率需要达到95.5%以上才能够发文章。下载地址： [http://www.nada.kth.se/cvap/actions/][http_www.nada.kth.se_cvap_actions]

3. INRIA XMAX多视角视频库

该数据库从五个视角获得，一共11个人执行14种行为。室内四个方向和头顶一共安装5个摄像头。另外背景和光照基本不变。下载地址： [http://4drepository.inrialpes.fr/public/viewgroup/6][http_4drepository.inrialpes.fr_public_viewgroup_6]

4. UCF Sports 数据库

该视频包括150段关于体育的视频，一共有13个动作。实验室采用留一交叉验证法。2011年cvpr有几篇都用这个数据库，正确率要达到87%才能发文章。下载地址： [http://vision.eecs.ucf.edu/data.html][http_vision.eecs.ucf.edu_data.]

5. Hollywood 人体行为库

该数据库包括8类行为。这些都是电影中的片段。

下载地址： [http://www.di.ens.fr/~laptev/actions/hollywood2/][http_www.di.ens.fr_laptev_actions_hollywood2]

6. Olympic sports dataset

该数据库有16种行为，783段视频。现在的正确率大约在75%左右。

下载地址： [http://vision.stanford.edu/Datasets/OlympicSports/][http_vision.stanford.edu_Datasets_OlympicSports]

7. UIUC action dataset

这个数据库已经做到98%了，建议不要去做了。下载地址： [http://vision.cs.uiuc.edu/projects/activity][http_vision.cs.uiuc.edu_projects_activity] [/][http_vision.cs.uiuc.edu_projects_activity]

ComputerVision中一些常用的图像数据库

Database OverviewSurveys

[http://emotion-research.net/wiki/Databases][http_emotion-research.net_wiki_Databases]

AR Face Database (AR):

[http://rvl1.ecn.purdue.edu/~aleix/aleix\_face\_DB.html][http_rvl1.ecn.purdue.edu_aleix_aleix_face_DB.html]

BioID Face Database(BioID):

[http://www.humanscan.de/support/downloads/facedb.php][http_www.humanscan.de_support_downloads_facedb.php]

Brodatz Texture Database(Brodatz):

Butterfly Database(BDB):

[http://www-cvr.ai.uiuc.edu/ponce\_grp/data][http_www-cvr.ai.uiuc.edu_ponce_grp_data]

CMU Frontal FaceDatabase (CMUFF):

[http://vasc.ri.cmu.edu//idb/html/face/frontal\_images/index.html][http_vasc.ri.cmu.edu_idb_html_face_frontal_images_index.html]

CMU PIE Database(CMUPIE):

[http://www.ri.cmu.edu/projects/project\_418.html][http_www.ri.cmu.edu_projects_project_418.html]

CMU Profile FaceDatabase (CMUPF):

[http://vasc.ri.cmu.edu//idb/html/face/profile\_images/index.html][http_vasc.ri.cmu.edu_idb_html_face_profile_images_index.html]

Columbia-UtrechtReflectance and Texture Database(CUReT):

Corel Gallery Magic65000 (CGM):

CVL Database (CVL):http://www.lrv.fri.uni-lj.si/facedb.html

Data Becker 222222Premium Cliparts (DBPC):

M2VTS Multimodal FaceDatabase ():

[http://www.tele.ucl.ac.be/PROJECTS/M2VTS/m2fdb.html][http_www.tele.ucl.ac.be_PROJECTS_M2VTS_m2fdb.html]

MIT CBCL Car Database(MITC):

[http://cbcl.mit.edu/cbcl/software-datasets/CarData.html][http_cbcl.mit.edu_cbcl_software-datasets_CarData.html]

MIT CBCL Face Database(MITF):

[http://cbcl.mit.edu/cbcl/software-datasets/FaceData2.html][http_cbcl.mit.edu_cbcl_software-datasets_FaceData2.html]

MIT CBCL FaceRecognition Database ():

[http://cbcl.mit.edu/software-datasets/heisele/facerecognition-database.html][http_cbcl.mit.edu_software-datasets_heisele_facerecognition-database.html]

MIT CBCL PedestrianDatabase (MITP):

[http://cbcl.mit.edu/cbcl/software-datasets/PedestrianData.html][http_cbcl.mit.edu_cbcl_software-datasets_PedestrianData.html]

Object RecognitionDatabase (ORDB):

[http://www-cvr.ai.uiuc.edu/ponce\_grp/data][http_www-cvr.ai.uiuc.edu_ponce_grp_data]

ORL Database of Faces(ORL):http://www.uk.research.att.com/facedatabase.html

OUTex (OUTex):

PETS 2000 Dataset (PETS2000): [ftp://ftp.pets.rdg.ac.uk/pub/PETS2000/][ftp_ftp.pets.rdg.ac.uk_pub_PETS2000]

PETS 2001 Dataset(PETS2001):

[http://www.cvg.cs.rdg.ac.uk/PETS2001/pets2001-dataset.html][http_www.cvg.cs.rdg.ac.uk_PETS2001_pets2001-dataset.html]

PETS 2002 Dataset(PETS2002):

[http://www.cvg.cs.rdg.ac.uk/PETS2002/pets2002-db.html][http_www.cvg.cs.rdg.ac.uk_PETS2002_pets2002-db.html]

PETS 2005 Dataset(PETS2005):

[http://www.cvg.cs.rdg.ac.uk/PETS-ICVS/pets-icvs-db.html][http_www.cvg.cs.rdg.ac.uk_PETS-ICVS_pets-icvs-db.html]

PETS-ECCV 2004 Dataset(PETSECCV2004):

PETS-ICVS 2003 Dataset(PETSICVS2003):

PETS汇总 [http://www.hitech-projects.com/euprojects/cantata/datasets\_cantata/dataset.html][http_www.hitech-projects.com_euprojects_cantata_datasets_cantata_dataset.html]

PhoTex (PhoTex):

Pilot European ImageProcessing Archive (PEIPA):

[http://peipa.essex.ac.uk/][http_peipa.essex.ac.uk]

Talking Face Video ():

Texture Database (TDB):

[http://www-cvr.ai.uiuc.edu/ponce\_grp/data][http_www-cvr.ai.uiuc.edu_ponce_grp_data]

Texture Database for theMeasurement of Textureclassification algorithms (MeasTex):

The Color FERET Database():

[http://www.itl.nist.gov/iad/humanid/colorferet/home.html][http_www.itl.nist.gov_iad_humanid_colorferet_home.html]

The Extended M2VTSDatabase (XM2VTSDB ):

[http://www.ee.surrey.ac.uk/Research/VSSP/xm2vtsdb/][http_www.ee.surrey.ac.uk_Research_VSSP_xm2vtsdb]

The FERET Database ():

[http://www.itl.nist.gov/iad/humanid/feret/][http_www.itl.nist.gov_iad_humanid_feret]

The Japanese FemaleFacial Expression (JAFFE)Database (JAFFE):

[http://www.mis.atr.co.jp/~mlyons/jaffe.html][http_www.mis.atr.co.jp_mlyons_jaffe.html]

The M2VTS Database (M2VTS): [http://www.tele.ucl.ac.be/PROJECTS/M2VTS/m2fdb.html][http_www.tele.ucl.ac.be_PROJECTS_M2VTS_m2fdb.html]

The Psychological ImageCollection at Stirling(PICS):

[http://pics.psych.stir.ac.uk/cgi-bin/PICS/New/pics.cgi][http_pics.psych.stir.ac.uk_cgi-bin_PICS_New_pics.cgi]

The UMIST Face Database(UMIST):

[http://images.ee.umist.ac.uk/danny/database.html][http_images.ee.umist.ac.uk_danny_database.html]

The University of OuluPhysics-Based FaceDatabase (UOFD):

[http://www.ee.oulu.fi/research/imag/color/pbfd.html][http_www.ee.oulu.fi_research_imag_color_pbfd.html]

The Yale Face Database(YFD):

[http://cvc.yale.edu/projects/yalefaces/yalefaces.html][http_cvc.yale.edu_projects_yalefaces_yalefaces.html]

The Yale Face Database B(YFDB):

[http://cvc.yale.edu/projects/yalefacesB/yalefacesB.html][http_cvc.yale.edu_projects_yalefacesB_yalefacesB.html]

Vision Texture Database(VisTex):

VS-PETS 2003 Dataset(VSPETS2003):

[微软剑桥研究院kinect姿势识别数据库][kinect]:

[http://research.microsoft.com/en-us/downloads/4e1c9174-9b94-4c4d-bc5e-0a9c929869a7/default.aspx][http_research.microsoft.com_en-us_downloads_4e1c9174-9b94-4c4d-bc5e-0a9c929869a7_default.aspx]

深度图像处理数据库

http://www.mmk.ei.tum.de/layout.php?LangExt=&selectedMain=Verschiedenes&selectedSub=TUMGAIT2\#downl