机器视觉中常用的数据测试集

【转】 机器视觉中常用的数据测试集

计算机视觉数据集

WallFlower dataset: 用于评价背景建模算法的好坏. Ground-truth foreground provided. 
Foreground/Background segmentation and Stereo dataset: from Microsoft Cambridge. 
VISOR: Video Surveillance Online Repositiory: 大量的视频和路面实况. 
3D Photography Dataset
Multi-model, multi-camera meeting room dataset
Advanced Video and Signal based Surveillance: 各种用于跟踪和检测的数据集. 
Caltech image collections: 用于目标物体检测,分割和分类
INRIA Datasets: 车辆, 人, 马, 人类行为等 
CAVIAR surveillance Dataset
Videos for Head Tracking
Pedestrian dataset from MIT
Shadow detection datasets
Flash and non-Flash dataset
Experiments on skin region detection and tracking: 包括一个ground-truthed dataset
MIT Face Dataset
MIT Car Datasets
MIT Street Scenes: CBCL StreetScenes Challenge Framework 是一个图像、注释、软件和性能检测的对象集[cars, pedestrians, bicycles, buildings, trees, skies, roads, sidewalks, and stores] 
LabelMe Dataset: 超过150,000已经标注的照片. 
MuHAVi: Multicamera Human Action Video DataA large body of human action video data using 8 cameras. Includes manually annotated silhouette data. 用于测试人行为的数据集
INRIA Xmas Motion Acquisition Sequences (IXMAS): Multiview dataset for view-invariant human action recognition. 
i-LIDS datasets: UK Government benchmark datasets for automated surveillance. 
The Daimler Pedestrian Detection Benchmark: contains 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. 
Stereo Pedestrian Detection Evaluation Dataset: a dataset for evaluating pedestrian detection using stereo camera images and video. 用于测试行人检测算法的数据集
Colour video and Thermal infrared datasets: Dataset of videos in colour and thermal infrared. Videos are aligned temporally and spatially. Ground-truth for object tracking is provided.

http://hi.baidu.com/56908268/blog/item/4f9fc51b4e662ff6af51338a.html

 

 

Datasets

  • MIT CSAIL LabelMe, open annotation tool  related tech report

  • PASCAL Visual Object Classes challenges (2005-2007)

  • Wordnet

  • Caltech101

  • Caltech256

  • TREC Video Retrieval Evaluation

  • Oxford buildings dataset

  • Photo-tourism patches

  • UIUC Car detection dataset

  • CMU Face databases

  • Animals on the Web data

  • ETH-80

  • Graz 02

  • MIT Objects and Scenes

  • NYU NORB dataset

  • Columbia COIL

  • Oxford flowers dataset

  • SFU activity dataset (sports)

  • Princeton events dataset

  • Weizmann activity videos  
  • Data collections of detected faces, from Oxford VGG

  • Face data from Buffy episode, from Oxford VGG

  • University of Cambridge face data from films [go to Data link]

  • Reuters

  • Dataset list from the Computer Vision Homepage

  • Image Parsing

  • Various other datasets from the Oxford Visual Geometry group

  • INRIA Holiday images dataset

  • Movie human actions dataset from Laptev et al.

  • ESP game dataset
  • Bastian Leibe’s dataset page: pedestrians, vehicles, cows, etc.

  • UMass Labeled Faces in the Wild

  • FaceTracer database from Columbia

 

 

 

WallFlower dataset: For evaluating background modelling algorithms. Ground-truth foreground provided. 
Foreground/Background segmentation and Stereo dataset: from Microsoft Cambridge. 
VISOR: Video Surveillance Online Repositiory: Lots of videos and ground truth. 
3D Photography Dataset 
Multi-model, multi-camera meeting room dataset 
Advanced Video and Signal based Surveillance: a variety datasets for tracking and detection. 
Caltech image collections: object detection, segmentation and classification 
INRIA Datasets: Cars, people, horses, human actions, etc. 
CAVIAR surveillance Dataset 
Videos for Head Tracking 
Pedestrian dataset from MIT 
Shadow detection datasets 
Flash and non-Flash dataset 
Experiments on skin region detection and tracking: it includes a ground-truthed dataset 
MIT Face Dataset 
MIT Car Datasets 
MIT Street Scenes: CBCL StreetScenes Challenge Framework is a collection of images, annotations, software and performance measures for object detection [cars, pedestrians, bicycles, buildings, trees, skies, roads, sidewalks, and stores] 
LabelMe Dataset: Over 150,000 images with objects annotated and labelled. 
MuHAVi: Multicamera Human Action Video DataA large body of human action video data using 8 cameras. Includes manually annotated silhouette data. 
INRIA Xmas Motion Acquisition Sequences (IXMAS): Multiview dataset for view-invariant human action recognition. 
i-LIDS datasets: UK Government benchmark datasets for automated surveillance. 
The Daimler Pedestrian Detection Benchmark: contains 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. 
Stereo Pedestrian Detection Evaluation Dataset: a dataset for evaluating pedestrian detection using stereo camera images and video. 
Colour video and Thermal infrared datasets: Dataset of videos in colour and thermal infrared. Videos are aligned temporally and spatially. Ground-truth for object tracking is provided. 

Dataset lists 
List of Databases: Includes multiple face datasets, texture datasets, etc. 
UIUC Datasets: Includes... Fifteen Scene Categories, 3D Object Recognition Stereo Dataset, 3D Photography Dataset, Visual Datasets, Birds, Butterflies, Object Recognition Database, Texture Database and Video Sequences. 
OTCBVS Datasets: Several datasets that include non-visual data, such as thermal infrared and NIR. 
List of "emotional" databases:

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