計算機視覺常用開源庫
– Implementation of a unified approach for face detection, pose estimation, and landmark localization (CVPR 2012).
Attributes and Semantic Features
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– Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).
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– Implementation of object bank semantic features (NIPS 2010). See also
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– Software for extracting high-level image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).
Large-Scale Learning
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– Source code for fast additive kernel SVM classifiers (PAMI 2013).
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– Library for large-scale linear SVM classification.
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– Implementation for Pegasos SVM and Homogeneous Kernel map.
Fast Indexing and Image Retrieval
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FLANN – Library for performing fast approximate nearest neighbor.
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– Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).
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– Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing (CVPR 2011).
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– Efficient code for state-of-the-art large-scale image retrieval (CVPR 2011).
Object Detection
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– Very fast and accurate pedestrian detector (CVPR 2012).
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– Excellent resource for pedestrian detection, with various links for state-of-the-art implementations.
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– Enhanced implementation of Viola&Jones real-time object detector, with trained models for face detection.
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– Source code for branch-and-bound optimization for efficient object localization (CVPR 2008).
3D Recognition
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– Library for 3D image and point cloud processing.
Action Recognition
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– Source code for action recognition based on the ActionBank representation (CVPR 2012).
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– software for computing space-time interest point descriptors
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- C++ code for activity recognition using the velocity histories of tracked keypoints (ICCV 2009)
Datasets
Attributes
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– 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.
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– Attribute annotations for images collected from Yahoo and Pascal VOC 2008.
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– 15,000 faces annotated with 10 attributes and fiducial points.
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– 58,797 face images of 200 people with 73 attribute classifier outputs.
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– 13,233 face images of 5,749 people with 73 attribute classifier outputs.
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– 8,000 people with annotated attributes. Check also this link for another dataset of human attributes.
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– Large-scale scene attribute database with a taxonomy of 102 attributes.
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– Variety of attribute labels for the ImageNet dataset.
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– Data for OSR and a subset of PubFig datasets. Check also this link for the WhittleSearch data.
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– Images of shopping categories associated with textual descriptions.
Fine-grained Visual Categorization
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– Hundreds of bird categories with annotated parts and attributes.
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– 20,000 images of 120 breeds of dogs from around the world.
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– 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is included.
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– 832 images of 10 species of butterflies.
Face Detection
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– UMass face detection dataset and benchmark (5,000+ faces)
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– Classical face detection dataset.
Face Recognition
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– Large collection of face recognition datasets.
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– UMass unconstrained face recognition dataset (13,000+ face images).
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– includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.
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– contains more than 750,000 images of 337 people, with 15 different views and 19 lighting conditions.
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FERET – Classical face recognition dataset.
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– Easy to use if you want play with simple face datasets including Yale, ORL, PIE, and Extended Yale B.
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– Low-resolution face dataset captured from surveillance cameras.
Handwritten Digits
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MNIST – large dataset containing a training set of 60,000 examples, and a test set of 10,000 examples.
Pedestrian Detection
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– 10 hours of video taken from a vehicle,350K bounding boxes for about 2.3K unique pedestrians.
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– Currently one of the most popular pedestrian detection datasets.
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– Urban dataset captured from a stereo rig mounted on a stroller.
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– Dataset with image pairs recorded in an crowded urban setting with an onboard camera.
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– One of 20 categories in PASCAL VOC detection challenges.
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– Small dataset captured from surveillance cameras.
Generic Object Recognition
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– Currently the largest visual recognition dataset in terms of number of categories and images.
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– 80 million 32x32 low resolution images.
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– One of the most influential visual recognition datasets.
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/ – Popular image datasets containing 101 and 256 object categories, respectively.
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– Online annotation tool for building computer vision databases.
Scene Recognition
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– MIT scene understanding dataset.
Feature Detection and Description
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– Widely used dataset for measuring performance of feature detection and description. Checkfor an evaluation framework.
Action Recognition
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– CVPR 2012 tutorial covering various datasets for action recognition.
RGBD Recognition
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– Dataset containing 300 common household objects
Reference:
特徵提取 機器視覺 綜合程式碼 主頁程式碼 行人檢測 視覺壁障 物體檢測演算法 人臉檢測 ICA獨立成分分析 濾波演算法 路面識別 分割演算法
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MATLAB Normalized Cuts Segmentation Code:
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