常用计算机视觉实验图像库和图像集

原文：http://blog.csdn.net/lansatiankongxxc/article/details/12978207

1.搜狗实验室数据集：

http://www.sogou.com/labs/dl/p.html

互联网图片库来自sogou图片搜索所索引的部分数据。其中收集了包括人物、动物、建筑、机械、风景、运动等类别，总数高达2,836,535张图片。对于每张图片，数据集中给出了图片的原图、缩略图、所在网页以及所在网页中的相关文本。200多G

2

http://www.imageclef.org/

IMAGECLEF致力于位图片相关领域提供一个基准（检索、分类、标注等等）Cross Language Evaluation Forum (CLEF)。从2003年开始每年举行一次比赛.

http://staff.science.uva.nl/~xirong/index.php?n=Main.Dataset

3

Xiaorong Li 维护的数据集。PhD ,Intelligent Systems Lab Amsterdam.research on video and image retrieval.

Flickr-3.5M: A collection of 3.5 million social-tagged images.
Social20: A ground-truth set for tag-based social image retrieval.
Biconcepts2012test: A ground-truth set for retrieving bi-concepts (concept pairs) in unlabeled images.
neg4free: A set of negative examples automatically harvested from social-tagged images for 20 PASCAL VOC concepts.

4

wikipedia featured articles 函数图片（以及特征）以及对应的wiki文本。可以看看文章A New Approach to Cross-Modal Multimedia Retrieval，还有一批文章On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval不过还没有下载链接

http://www.svcl.ucsd.edu/projects/crossmodal/

5

http://lms.comp.nus.edu.sg/research/NUS-WIDE.htm

To our knowledge, this is the largest real-world web image dataset comprising over 269,000 images with over 5,000 user-provided tags, and ground-truth of 81 concepts for the entire dataset. The dataset is much larger than the popularly available Corel and Caltech 101 datasets. Though some datasets comprise over 3 million images, they only have ground-truth for a small fraction of images. Our proposed NUS-WIDE dataset has the ground-truth for the entire dataset.

6.

http://www.cs.washington.edu/research/imagedatabase/

7.

http://lear.inrialpes.fr/~jegou/data.php

Jegou的数据集，不过Jegou是专门做CBIR的，图像有ground truth，没有标注。

8.

http://www.robots.ox.ac.uk/~vgg/data/oxbuildings/

vgg的osford building dataset。也是专门CBIR的数据。

9.

http://acmmm13.org/submissions/call-for-multimedia-grand-challenge-solutions/msr-bing-grand-challenge-on-image-retrieval-scientific-track/

The dataset for the Microsoft Image Grand Challenge on Image Retrieval

另外介绍cvpaper上的整理的数据集

http://www.cvpapers.com/index.html

Participate in Reproducible Research

Detection

PASCAL VOC 2009 dataset: Classification/Detection Competitions, Segmentation Competition, Person Layout Taster Competition datasets
LabelMe dataset: LabelMe is a web-based image annotation tool that allows researchers to label images and share the annotations with the rest of the; community. If you use the database, we only ask that you contribute to it, from time to time, by using the labeling tool.
BioID Face Detection Database: 1521 images with human faces, recorded under natural conditions, i.e. varying illumination and complex background. The eye positions; have been set manually.
CMU/VASC & PIE Face dataset
Yale Face dataset
Caltech: Cars, Motorcycles, Airplanes, Faces, Leaves, Backgrounds
Caltech 101: Pictures of objects belonging to 101 categories
Caltech 256: Pictures of objects belonging to 256 categories
Daimler Pedestrian Detection Benchmark: 15,560 pedestrian and non-pedestrian samples (image cut-outs) and 6744 additional full images not containing pedestrians for; bootstrapping. The test set contains more than 21,790 images with 56,492 pedestrian labels (fully visible or partially occluded),; captured from a vehicle in urban traffic.
MIT Pedestrian dataset: CVC Pedestrian Datasets
CVC Pedestrian Datasets: CBCL Pedestrian Database
MIT Face dataset: CBCL Face Database
MIT Car dataset: CBCL Car Database
MIT Street dataset: CBCL Street Database
INRIA Person Data Set: A large set of marked up images of standing or walking people
INRIA car dataset: A set of car and non-car images taken in a parking lot nearby INRIA
INRIA horse dataset: A set of horse and non-horse images
H3D Dataset: 3D skeletons and segmented regions for 1000 people in images
HRI RoadTraffic dataset: A large-scale vehicle detection dataset
BelgaLogos: 10000 images of natural scenes, with 37 different logos, and 2695 logos instances, annotated with a bounding box.
FlickrBelgaLogos: 10000 images of natural scenes grabbed on Flickr, with 2695 logos instances cut and pasted from the BelgaLogos dataset.
FlickrLogos-32: The dataset FlickrLogos-32 contains photos depicting logos and is meant for the evaluation of multi-class logo detection/recognition; as well as logo retrieval methods on real-world images. It consists of 8240 images downloaded from Flickr.
TME Motorway Dataset: 30000+ frames with vehicle rear annotation and classification (car and trucks) on motorway/highway sequences. Annotation; semi-automatically generated using laser-scanner data. Distance estimation and consistent target ID over time available.
PHOS (Color Image Database for illumination invariant feature selection): Phos is a color image database of 15 scenes captured under different illumination conditions. More particularly, every scene; of the database contains 15 different images: 9 images captured under various strengths of uniform illumination, and 6 images; under different degrees of non-uniform illumination. The images contain objects of different shape, color and texture and can; be used for illumination invariant feature detection and selection.
CaliforniaND: An Annotated Dataset For Near-Duplicate Detection In Personal Photo Collections: California-ND contains 701 photos taken directly from a real user's personal photo collection, including many challenging; non-identical near-duplicate cases, without the use of artificial image transformations. The dataset is annotated by 10 different; subjects, including the photographer, regarding near duplicates.

Classification

PASCAL VOC 2009 dataset: Classification/Detection Competitions, Segmentation Competition, Person Layout Taster Competition datasets
Caltech: Cars, Motorcycles, Airplanes, Faces, Leaves, Backgrounds
Caltech 101: Pictures of objects belonging to 101 categories
Caltech 256: Pictures of objects belonging to 256 categories
ETHZ Shape Classes: A dataset for testing object class detection algorithms. It contains 255 test images and features five diverse shape-based; classes (apple logos, bottles, giraffes, mugs, and swans).
Flower classification data sets: 17 Flower Category Dataset
Animals with attributes: A dataset for Attribute Based Classification. It consists of 30475 images of 50 animals classes with six pre-extracted; feature representations for each image.
Stanford Dogs Dataset: Dataset of 20,580 images of 120 dog breeds with bounding-box annotation, for fine-grained image categorization.

Recognition

Face and Gesture Recognition Working Group FGnet: Face and Gesture Recognition Working Group FGnet
Feret: Face and Gesture Recognition Working Group FGnet
PUT face: 9971 images of 100 people
Labeled Faces in the Wild: A database of face photographs designed for studying the problem of unconstrained face recognition
Urban scene recognition: Traffic Lights Recognition, Lara's public benchmarks.
PubFig: Public Figures Face Database: The PubFig database is a large, real-world face dataset consisting of 58,797 images of 200 people collected from the internet.; Unlike most other existing face datasets, these images are taken in completely uncontrolled situations with non-cooperative subjects.
YouTube Faces: The data set contains 3,425 videos of 1,595 different people. The shortest clip duration is 48 frames, the longest clip is 6,070; frames, and the average length of a video clip is 181.3 frames.
MSRC-12: Kinect gesture data set: The Microsoft Research Cambridge-12 Kinect gesture data set consists of sequences of human movements, represented as; body-part locations, and the associated gesture to be recognized by the system.
QMUL underGround Re-IDentification (GRID) Dataset: This dataset contains 250 pedestrian image pairs + 775 additional images captured in a busy underground station for the research; on person re-identification.
Person identification in TV series: Face tracks, features and shot boundaries from our latest CVPR 2013 paper. It is obtained from 6 episodes of Buffy the Vampire; Slayer and 6 episodes of Big Bang Theory.
ChokePoint Dataset: ChokePoint is a video dataset designed for experiments in person identification/verification under real-world surveillance; conditions. The dataset consists of 25 subjects (19 male and 6 female) in portal 1 and 29 subjects (23 male and 6 female) in portal 2.

Tracking

BIWI Walking Pedestrians dataset: Walking pedestrians in busy scenarios from a bird eye view
"Central" Pedestrian Crossing Sequences: Three pedestrian crossing sequences
Pedestrian Mobile Scene Analysis: The set was recorded in Zurich, using a pair of cameras mounted on a mobile platform. It contains 12'298 annotated pedestrians; in roughly 2'000 frames.
Head tracking: BMP image sequences.
KIT AIS Dataset: Data sets for trackingvehiclesandpeoplein aerial image sequences.
MIT Traffic Data Set: MIT traffic data set is for research on activity analysis and crowded scenes. It includes a traffic video sequence of 90 minutes; long. It is recorded by a stationary camera.

Segmentation

Image Segmentation with A Bounding Box Prior dataset: Ground truth database of 50 images with: Data, Segmentation, Labelling - Lasso, Labelling - Rectangle
PASCAL VOC 2009 dataset: Classification/Detection Competitions, Segmentation Competition, Person Layout Taster Competition datasets
Motion Segmentation and OBJCUT data: Cows for object segmentation, Five video sequences for motion segmentation
Geometric Context Dataset: Geometric Context Dataset: pixel labels for seven geometric classes for 300 images
Crowd Segmentation Dataset: This dataset contains videos of crowds and other high density moving objects. The videos are collected mainly from the BBC; Motion Gallery and Getty Images website. The videos are shared only for the research purposes. Please consult the terms and; conditions of use of these videos from the respective websites.
CMU-Cornell iCoseg Dataset: Contains hand-labelled pixel annotations for 38 groups of images, each group containing a common foreground. Approximately; 17 images per group, 643 images total.
Segmentation evaluation database: 200 gray level images along with ground truth segmentations
The Berkeley Segmentation Dataset and Benchmark: Image segmentation and boundary detection. Grayscale and color segmentations for 300 images, the images are divided into; a training set of 200 images, and a test set of 100 images.
Weizmann horses: 328 side-view color images of horses that were manually segmented. The images were randomly collected from the WWW.
Saliency-based video segmentation with sequentially updated priors: 10 videos as inputs, and segmented image sequences as ground-truth

Foreground/Background

Wallflower Dataset: For evaluating background modelling algorithms
Foreground/Background Microsoft Cambridge Dataset: Foreground/Background segmentation and Stereo dataset from Microsoft Cambridge
Stuttgart Artificial Background Subtraction Dataset: The SABS (Stuttgart Artificial Background Subtraction) dataset is an artificial dataset for pixel-wise evaluation of; background models.

Saliency Detection (source)

AIM: 120 Images / 20 Observers (Neil D. B. Bruce and John K. Tsotsos 2005).
LeMeur: 27 Images / 40 Observers (O. Le Meur, P. Le Callet, D. Barba and D. Thoreau 2006).
Kootstra: 100 Images / 31 Observers (Kootstra, G., Nederveen, A. and de Boer, B. 2008).
DOVES: 101 Images / 29 Observers (van der Linde, I., Rajashekar, U., Bovik, A.C., Cormack, L.K. 2009).
Ehinger: 912 Images / 14 Observers (Krista A. Ehinger, Barbara Hidalgo-Sotelo, Antonio Torralba and Aude Oliva 2009).
NUSEF: 758 Images / 75 Observers (R. Subramanian, H. Katti, N. Sebe1, M. Kankanhalli and T-S. Chua 2010).
JianLi: 235 Images / 19 Observers (Jian Li, Martin D. Levine, Xiangjing An and Hangen He 2011).
Extended Complex Scene Saliency Dataset (ECSSD): ECSSD contains 1000 natural images with complex foreground or background. For each image, the ground truth mask of; salient object(s) is provided.

Video Surveillance

CAVIAR: For the CAVIAR project a number of video clips were recorded acting out the different scenarios of interest. These include; people walking alone, meeting with others, window shopping, entering and exitting shops, fighting and passing out and last,; but not least, leaving a package in a public place.
ViSOR: ViSOR contains a large set of multimedia data and the corresponding annotations.

Multiview

3D Photography Dataset: Multiview stereo data sets: a set of images
Multi-view Visual Geometry group's data set: Dinosaur, Model House, Corridor, Aerial views, Valbonne Church, Raglan Castle, Kapel sequence
Oxford reconstruction data set (building reconstruction): Oxford colleges
Multi-View Stereo dataset (Vision Middlebury): Temple, Dino
Multi-View Stereo for Community Photo Collections: Venus de Milo, Duomo in Pisa, Notre Dame de Paris
IS-3D Data: Dataset provided by Center for Machine Perception
CVLab dataset: CVLab dense multi-view stereo image database
3D Objects on Turntable: Objects viewed from 144 calibrated viewpoints under 3 different lighting conditions
Object Recognition in Probabilistic 3D Scenes: Images from 19 sites collected from a helicopter flying around Providence, RI. USA. The imagery contains approximately; a full circle around each site.
Multiple cameras fall dataset: 24 scenarios recorded with 8 IP video cameras. The first 22 first scenarios contain a fall and confounding events, the last 2; ones contain only confounding events.

Action

UCF Sports Action Dataset: This dataset consists of a set of actions collected from various sports which are typically featured on broadcast television; channels such as the BBC and ESPN. The video sequences were obtained from a wide range of stock footage websites; including BBC Motion gallery, and GettyImages.
UCF Aerial Action Dataset: This dataset features video sequences that were obtained using a R/C-controlled blimp equipped with an HD camera mounted; on a gimbal.The collection represents a diverse pool of actions featured at different heights and aerial viewpoints. Multiple; instances of each action were recorded at different flying altitudes which ranged from 400-450 feet and were performed by; different actors.
UCF YouTube Action Dataset: It contains 11 action categories collected from YouTube.
Weizmann action recognition: Walk, Run, Jump, Gallop sideways, Bend, One-hand wave, Two-hands wave, Jump in place, Jumping Jack, Skip.
UCF50: UCF50 is an action recognition dataset with 50 action categories, consisting of realistic videos taken from YouTube.
ASLAN: The Action Similarity Labeling (ASLAN) Challenge.
MSR Action Recognition Datasets: The dataset was captured by a Kinect device. There are 12 dynamic American Sign Language (ASL) gestures, and 10 people.; Each person performs each gesture 2-3 times.
KTH Recognition of human actions: Contains six types of human actions (walking, jogging, running, boxing, hand waving and hand clapping) performed several; times by 25 subjects in four different scenarios: outdoors, outdoors with scale variation, outdoors with different clothes and; indoors.
Hollywood-2 Human Actions and Scenes dataset: Hollywood-2 datset contains 12 classes of human actions and 10 classes of scenes distributed over 3669 video clips and; approximately 20.1 hours of video in total.
Collective Activity Dataset: This dataset contains 5 different collective activities : crossing, walking, waiting, talking, and queueing and 44 short video; sequences some of which were recorded by consumer hand-held digital camera with varying view point.
Olympic Sports Dataset: The Olympic Sports Dataset contains YouTube videos of athletes practicing different sports.
SDHA 2010: Surveillance-type videos
VIRAT Video Dataset: The dataset is designed to be realistic, natural and challenging for video surveillance domains in terms of its resolution,; background clutter, diversity in scenes, and human activity/event categories than existing action recognition datasets.
HMDB: A Large Video Database for Human Motion Recognition: Collected from various sources, mostly from movies, and a small proportion from public databases, YouTube and Google; videos. The dataset contains 6849 clips divided into 51 action categories, each containing a minimum of 101 clips.
Stanford 40 Actions Dataset: Dataset of 9,532 images of humans performing 40 different actions, annotated with bounding-boxes.
50Salads dataset: Fully annotated dataset of RGB-D video data and data from accelerometers attached to kitchen objects capturing 25 people; preparing two mixed salads each (4.5h of annotated data). Annotated activities correspond to steps in the recipe and include; phase (pre-/ core-/ post) and the ingredient acted upon.

Human pose/Expression

AFEW (Acted Facial Expressions In The Wild)/SFEW (Static Facial Expressions In The Wild): Dynamic temporal facial expressions data corpus consisting of close to real world environment extracted from movies.
ETHZ CALVIN Dataset

Image stitching

IPM Vision Group Image Stitching datasets: Images and parameters for registeration

Medical

VIP Laparoscopic / Endoscopic Dataset: Collection of endoscopic and laparoscopic (mono/stereo) videos and images

Misc

Zurich Buildings Database: ZuBuD Image Database contains over 1005 images about Zurich city building.
Color Name Data Sets
Mall dataset: The mall dataset was collected from a publicly accessible webcam for crowd counting and activity profiling research.
QMUL Junction Dataset: A busy traffic dataset for research on activity analysis and behaviour understanding.

CVOnline的数据集

http://homepages.inf.ed.ac.uk/rbf/CVonline/CVentry.htm

Index by Topic

Action Databases

50 Salads- fully annotated 4.5 hour dataset of RGB-D video + accelerometer data, capturing 25 people preparing
two mixed salads each (Dundee University, Sebastian Stein)
ASLAN Action similarity labeling challengedatabase (Orit Kliper-Gross)
Berkeley MHAD: A Comprehensive Multimodal Human Action Database(Ferda Ofli)
BEHAVE Interacting Person Video Data with markup(Scott Blunsden, Bob Fisher, Aroosha Laghaee)
CVBASE06: annotated sports videos(Janez Pers)
G3D- synchronised video, depth and skeleton data for 20 gaming actions captured with Microsoft Kinect (Victoria Bloom)
Hollywood 3D- 650 3D action recognition in the wild videos, 14 action classes (Simon Hadfield)
Human Actions and Scenes Dataset(Marcin Marszalek, Ivan Laptev, Cordelia Schmid)
HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion (Brown University)
i3DPost Multi-View Human Action Datasets(Hansung Kim)
i-LIDS video event image dataset (Imagery library for intelligent detection systems)(Paul Hosner)
INRIA Xmas Motion Acquisition Sequences (IXMAS)(INRIA)
JPL First-Person Interaction dataset- 7 types of human activity videos taken from a first-person viewpoint (Michael S. Ryoo, JPL)
KTH human action recognition database(KTH CVAP lab)
LIRIS human activities dataset- 2 cameras, annotated, depth images (Christian Wolf, et al)
MuHAVi- Multicamera Human Action Video Data (Hossein Ragheb)
Oxford TV based human interactions(Oxford Visual Geometry Group)
Rochester Activities of Daily Living Dataset(Ross Messing)
SDHA Semantic Description of Human Activities 2010 contest - aerial views(Michael S. Ryoo, J. K. Aggarwal, Amit K. Roy-Chowdhury)
SDHA Semantic Description of Human Activities 2010 contest - Human Interactions(Michael S. Ryoo, J. K. Aggarwal, Amit K. Roy-Chowdhury)
TUM Kitchen Data Set of Everyday Manipulation Activities(Moritz Tenorth, Jan Bandouch)
TV Human Interaction Dataset(Alonso Patron-Perez)
Univ of Central Florida - Feature Films Action Dataset(Univ of Central Florida)
Univ of Central Florida - YouTube Action Dataset (sports)(Univ of Central Florida)
Univ of Central Florida - 50 Action Category Recognition in Realistic Videos (3 GB)(Kishore Reddy)
UCF 101 action dataset101 action classes, over 13k clips and 27 hours of video data (Univ of Central Florida)
Univ of Central Florida - Sports Action Dataset(Univ of Central Florida)
Univ of Central Florida - ARGAerial camera, Rooftop camera and Ground camera (UCF Computer Vision Lab)
UCR Videoweb Multi-camera Wide-Area Activities Dataset(Amit K. Roy-Chowdhury)
Verona Social interaction dataset(Marco Cristani)
Videoweb (multicamera) Activities Dataset(B. Bhanu, G. Denina, C. Ding, A. Ivers, A. Kamal, C. Ravishankar, A. Roy-Chowdhury, B. Varda)
ViHASi: Virtual Human Action Silhouette Data(userID: VIHASI password: virtual$virtual) (Hossein Ragheb, Kingston University)
WorkoutSU-10Kinect dataset for exercise actions (Ceyhun Akgul)
YouCook- 88 open-source YouTube cooking videos with annotations (Jason Corso)
WVU Multi-view action recognition dataset(Univ. of West Virginia)

Biological/Medical

Computed Tomography Emphysema Database(Lauge Sorensen)
Dermoscopy images(Eric Ehrsam)
DIADEM: Digital Reconstruction of Axonal and Dendritic Morphology Competition(Allen Institute for Brain Science et al)
DIARETDB1 - Standard Diabetic Retinopathy Database(Lappeenranta Univ of Technology)
DRIVE: Digital Retinal Images for Vessel Extraction(Univ of Utrecht)
MiniMammographic Database(Mammographic Image Analysis Society)
MIT CBCL Automated Mouse Behavior Recognition datasets(Nicholas Edelman)
Retinal fundus images - Ground truth of vascular bifurcations and crossovers(Univ of Groningen)
Spine and Cardiac data(Digital Imaging Group of London Ontario, Shuo Li)
Univ of Central Florida - DDSM: Digital Database for Screening Mammography(Univ of Central Florida)
VascuSynth- 120 3D vascular tree like structures with ground truth (Mengliu Zhao, Ghassan Hamarneh)
York Cardiac MRI dataset(Alexander Andreopoulos)

Face Databases

3D Mask Attack Database (3DMAD)- 76500 frames of 17 persons using Kinect RGBD with eye positions (Sebastien Marcel)
Audio-visual database for face and speaker recognition(Mobile Biometry MOBIO http://www.mobioproject.org/)
BANCA face and voice database(Univ of Surrey)
Binghampton Univ 3D static and dynamic facial expression database(Lijun Yin, Peter Gerhardstein and teammates)
BioID face database(BioID group)
Biwi 3D Audiovisual Corpus of Affective Communication- 1000 high quality, dynamic 3D scans of faces, recorded while pronouncing a set of English sentences.
CMU Facial Expression Database(CMU/MIT)
CMU/MIT Frontal Faces(CMU/MIT)
CMU/MIT Frontal Faces(CMU/MIT)
CMU Pose, Illumination, and Expression (PIE) Database(Simon Baker)
CSSE Frontal intensity and range images of faces(Ajmal Mian)
Face Recognition Grand Challenge datasets(FRVT - Face Recognition Vendor Test)
FaceTracer Database - 15,000 faces(Neeraj Kumar, P. N. Belhumeur, and S. K. Nayar)
FDDB: Face Detection Data set and Benchmark - studying unconstrained face detection(University of Massachusetts Computer Vision Laboratory)
FG-Net Aging Database of faces at different ages(Face and Gesture Recognition Research Network)
Facial Recognition Technology (FERET) Database(USA National Institute of Standards and Technology)
Hong Kong Face Sketch Database
Japanese Female Facial Expression (JAFFE) Database(Michael J. Lyons)
LFW: Labeled Faces in the Wild- unconstrained face recognition.Re-labeled Faces in the Wild- original images, but aligned using "deep funneling" method. (University of Massachusetts, Amherst)
Manchester Annotated Talking Face Video Dataset(Timothy Cootes)
MIT Collation of Face Databases(Ethan Meyers)
MORPH (Craniofacial Longitudinal Morphological Face Database)(University of North Carolina Wilmington)
MIT CBCL Face Recognition Database(Center for Biological and Computational Learning)
NIST mugshot identification database(USA National Institute of Standards and Technology)
ORL face database: 40 people with 10 views(ATT Cambridge Labs)
Oxford: faces, flowers, multi-view, buildings, object categories, motion segmentation, affine covariant regions, misc(Oxford Visual Geometry Group)
PubFig: Public Figures Face Database(Neeraj Kumar, Alexander C. Berg, Peter N. Belhumeur, and Shree K. Nayar)
SCface- Surveillance Cameras Face Database (Mislav Grgic, Kresimir Delac, Sonja Grgic, Bozidar Klimpak))
Trondheim Kinect RGB-D Person Re-identification Dataset(Igor Barros Barbosa)
UB KinFace Database- University of Buffalo kinship verification and recognition database
XM2VTS Face video sequences (295): The extended M2VTS Database (XM2VTS) -(Surrey University)
Yale Face Database - 11 expressions of 10 people(A. Georghaides)
Yale Face Database B - 576 viewing conditions of 10 people(A. Georghaides)

Fingerprints

FVC fingerpring verification competition 2002 dataset(University of Bologna)
FVC fingerpring verification competition 2004 dataset(University of Bologna)
FVC- a subset of FVC (Fingerprint Verification Competition) 2002 and 2004 fingerprint image databases, manually extracted minutiae data & associated documents (Umut Uludag)
NIST fingerprint databases(USA National Institute of Standards and Technology)
SPD2010 Fingerprint Singular Points Detection Competition(SPD 2010 committee)