机器视觉开源代码集合（转载）

一、特征提取Feature Extraction：

SIFT [1] [Demo
program][SIFT
Library] [VLFeat]

PCA-SIFT [2] [Project]

Affine-SIFT [3] [Project]

SURF [4] [OpenSURF]
[Matlab
Wrapper]

Affine Covariant Features [5] [Oxford
project]

MSER [6] [Oxford
project] [VLFeat]

Geometric Blur [7] [Code]

Local Self-Similarity Descriptor [8] [Oxford
implementation]

Global and Efficient Self-Similarity [9] [Code]

Histogram of Oriented Graidents [10] [INRIA
Object Localization Toolkit] [OLT
toolkit for Windows]

GIST [11] [Project]

Shape Context [12] [Project]

Color Descriptor [13] [Project]

Pyramids of Histograms of Oriented Gradients [Code]

Space-Time Interest Points (STIP) [14][Project]
[Code]

Boundary Preserving Dense Local Regions [15][Project]

Weighted Histogram[Code]

Histogram-based Interest Points Detectors[Paper][Code]

An OpenCV - C++ implementation of Local Self Similarity Descriptors [Project]

Fast Sparse Representation with Prototypes[Project]

Corner Detection [Project]

AGAST Corner Detector: faster than FAST and even FAST-ER[Project]

Real-time Facial Feature Detection using Conditional Regression Forests[Project]

Global and Efficient Self-Similarity for Object Classification and Detection[code]

WαSH: Weighted α-Shapes for Local Feature Detection[Project]

HOG[Project]

Online Selection of Discriminative Tracking Features[Project]

二、图像分割Image Segmentation：

Normalized Cut [1] [Matlab
code]

Gerg Mori’ Superpixel code [2] [Matlab
code]

Efficient Graph-based Image Segmentation [3] [C++
code] [Matlab
wrapper]

Mean-Shift Image Segmentation [4] [EDISON
C++ code] [Matlab
wrapper]

OWT-UCM Hierarchical Segmentation [5] [Resources]

Turbepixels [6] [Matlab
code 32bit] [Matlab
code 64bit] [Updated
code]

Quick-Shift [7] [VLFeat]

SLIC Superpixels [8] [Project]

Segmentation by Minimum Code Length [9] [Project]

Biased Normalized Cut [10] [Project]

Segmentation Tree [11-12] [Project]

Entropy Rate Superpixel Segmentation [13] [Code]

Fast Approximate Energy Minimization via Graph Cuts[Paper][Code]

Efficient Planar Graph Cuts with Applications in Computer Vision[Paper][Code]

Isoperimetric Graph Partitioning for Image Segmentation[Paper][Code]

Random Walks for Image Segmentation[Paper][Code]

Blossom V: A new implementation of a minimum cost perfect matching algorithm[Code]

An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision[Paper][Code]

Geodesic Star Convexity for Interactive Image Segmentation[Project]

Contour Detection and Image Segmentation Resources[Project][Code]

Biased Normalized Cuts[Project]

Max-flow/min-cut[Project]

Chan-Vese Segmentation using Level Set[Project]

A Toolbox of Level Set Methods[Project]

Re-initialization Free Level Set Evolution via Reaction Diffusion[Project]

Improved C-V active contour model[Paper][Code]

A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction[Paper][Code]

Level Set Method Research by Chunming Li[Project]

ClassCut for Unsupervised Class Segmentation[code]

SEEDS: Superpixels Extracted via Energy-Driven Sampling [Project][other]

三、目标检测Object Detection：

A simple object detector with boosting [Project]

INRIA Object Detection and Localization Toolkit [1] [Project]

Discriminatively Trained Deformable Part Models [2] [Project]

Cascade Object Detection with Deformable Part Models [3] [Project]

Poselet [4] [Project]

Implicit Shape Model [5] [Project]

Viola and Jones’s Face Detection [6] [Project]

Bayesian Modelling of Dyanmic Scenes for Object Detection[Paper][Code]

Hand detection using multiple proposals[Project]

Color Constancy, Intrinsic Images, and Shape Estimation[Paper][Code]

Discriminatively trained deformable part models[Project]

Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD [Project]

Image Processing On Line[Project]

Robust Optical Flow Estimation[Project]

Where's Waldo: Matching People in Images of Crowds[Project]

Scalable Multi-class Object Detection[Project]

Class-Specific Hough Forests for Object Detection[Project]

Deformed Lattice Detection In Real-World Images[Project]

Discriminatively trained deformable part models[Project]

四、显著性检测Saliency Detection：

Itti, Koch, and Niebur’ saliency detection [1] [Matlab
code]

Frequency-tuned salient region detection [2] [Project]

Saliency detection using maximum symmetric surround [3] [Project]

Attention via Information Maximization [4] [Matlab
code]

Context-aware saliency detection [5] [Matlab
code]

Graph-based visual saliency [6] [Matlab
code]

Saliency detection: A spectral residual approach. [7] [Matlab
code]

Segmenting salient objects from images and videos. [8] [Matlab
code]

Saliency Using Natural statistics. [9] [Matlab
code]

Discriminant Saliency for Visual Recognition from Cluttered Scenes. [10] [Code]

Learning to Predict Where Humans Look [11] [Project]

Global Contrast based Salient Region Detection [12] [Project]

Bayesian Saliency via Low and Mid Level Cues[Project]

Top-Down Visual Saliency via Joint CRF and Dictionary Learning[Paper][Code]

Saliency Detection: A Spectral Residual Approach[Code]

五、图像分类、聚类Image Classification, Clustering

Pyramid Match [1] [Project]

Spatial Pyramid Matching [2] [Code]

Locality-constrained Linear Coding [3] [Project]
[Matlab
code]

Sparse Coding [4] [Project]
[Matlab
code]

Texture Classification [5] [Project]

Multiple Kernels for Image Classification [6] [Project]

Feature Combination [7] [Project]

SuperParsing [Code]

Large Scale Correlation Clustering Optimization[Matlab
code]

Detecting and Sketching the Common[Project]

Self-Tuning Spectral Clustering[Project][Code]

User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior[Paper][Code]

Filters for Texture Classification[Project]

Multiple Kernel Learning for Image Classification[Project]

SLIC Superpixels[Project]

六、抠图Image Matting

A Closed Form Solution to Natural Image Matting [Code]

Spectral Matting [Project]

Learning-based Matting [Code]

七、目标跟踪Object Tracking：

A Forest of Sensors - Tracking Adaptive Background Mixture Models [Project]

Object Tracking via Partial Least Squares Analysis[Paper][Code]

Robust Object Tracking with Online Multiple Instance Learning[Paper][Code]

Online Visual Tracking with Histograms and Articulating Blocks[Project]

Incremental Learning for Robust Visual Tracking[Project]

Real-time Compressive Tracking[Project]

Robust Object Tracking via Sparsity-based Collaborative Model[Project]

Visual Tracking via Adaptive Structural Local Sparse Appearance Model[Project]

Online Discriminative Object Tracking with Local Sparse Representation[Paper][Code]

Superpixel Tracking[Project]

Learning Hierarchical Image Representation with Sparsity, Saliency and Locality[Paper][Code]

Online Multiple Support Instance Tracking [Paper][Code]

Visual Tracking with Online Multiple Instance Learning[Project]

Object detection and recognition[Project]

Compressive Sensing Resources[Project]

Robust Real-Time Visual Tracking using Pixel-Wise Posteriors[Project]

Tracking-Learning-Detection[Project][OpenTLD/C++
Code]

the HandVu：vision-based hand gesture interface[Project]

Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities[Project]

八、Kinect：

Kinect toolbox[Project]

OpenNI[Project]

zouxy09 CSDN Blog[Resource]

FingerTracker 手指跟踪[code]

九、3D相关：

3D Reconstruction of a Moving Object[Paper]
[Code]

Shape From Shading Using Linear Approximation[Code]

Combining Shape from Shading and Stereo Depth Maps[Project][Code]

Shape from Shading: A Survey[Paper][Code]

A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)[Project][Code]

Multi-camera Scene Reconstruction via Graph Cuts[Paper][Code]

A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination[Paper][Code]

Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture[Project]

Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers[Code]

Learning 3-D Scene Structure from a Single Still Image[Project]

十、机器学习算法：

Matlab class for computing Approximate Nearest Nieghbor (ANN) [Matlab
class providing interface toANN
library]

Random Sampling[code]

Probabilistic Latent Semantic Analysis (pLSA)[Code]

FASTANN and FASTCLUSTER for approximate k-means (AKM)[Project]

Fast Intersection / Additive Kernel SVMs[Project]

SVM[Code]

Ensemble learning[Project]

Deep Learning[Net]

Deep Learning Methods for Vision[Project]

Neural Network for Recognition of Handwritten Digits[Project]

Training a deep autoencoder or a classifier on MNIST digits[Project]

THE MNIST DATABASE of handwritten digits[Project]

Ersatz：deep neural networks in the cloud[Project]

Deep Learning [Project]

sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++[Project]

Weka 3: Data Mining Software in Java[Project]

Invited talk "A Tutorial on Deep Learning" by Dr. Kai Yu (余凯)[Video]

CNN - Convolutional neural network class[Matlab
Tool]

Yann LeCun's Publications[Wedsite]

LeNet-5, convolutional neural networks[Project]

Training a deep autoencoder or a classifier on MNIST digits[Project]

Deep Learning 大牛Geoffrey E. Hinton's HomePage[Website]

Multiple Instance Logistic Discriminant-based Metric Learning (MildML) and Logistic Discriminant-based Metric Learning (LDML)[Code]

Sparse coding simulation software[Project]

Visual Recognition and Machine Learning Summer School[Software]

十一、目标、行为识别Object, Action Recognition：

Action Recognition by Dense Trajectories[Project][Code]

Action Recognition Using a Distributed Representation of Pose and Appearance[Project]

Recognition Using Regions[Paper][Code]

2D Articulated Human Pose Estimation[Project]

Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression[Paper][Code]

Estimating Human Pose from Occluded Images[Paper][Code]

Quasi-dense wide baseline matching[Project]

ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms[Project]

Real Time Head Pose Estimation with Random Regression Forests[Project]

2D Action Recognition Serves 3D Human Pose Estimation[Project]

A Hough Transform-Based Voting Framework for Action Recognition[Project]

Motion Interchange Patterns for Action Recognition in Unconstrained Videos[Project]

2D articulated human pose estimation software[Project]

Learning and detecting shape models [code]

Progressive Search Space Reduction for Human Pose Estimation[Project]

Learning Non-Rigid 3D Shape from 2D Motion[Project]

十二、图像处理：

Distance Transforms of Sampled Functions[Project]

The Computer Vision Homepage[Project]

Efficient appearance distances between windows[code]

Image Exploration algorithm[code]

Motion Magnification 运动放大 [Project]

Bilateral Filtering for Gray and Color Images 双边滤波器 [Project]

A Fast Approximation of the Bilateral Filter using a Signal Processing Approach [Project]

十三、一些实用工具：

EGT: a Toolbox for Multiple View Geometry and Visual Servoing[Project]
[Code]

a development kit of matlab mex functions for OpenCV library[Project]

Fast Artificial Neural Network Library[Project]

十四、人手及指尖检测与识别：

finger-detection-and-gesture-recognition [Code]

Hand and Finger Detection using JavaCV[Project]

Hand and fingers detection[Code]

十五、场景解释：

Nonparametric Scene Parsing via Label Transfer [Project]

十六、光流Optical flow：

High accuracy optical flow using a theory for warping [Project]

Dense Trajectories Video Description [Project]

SIFT Flow: Dense Correspondence across Scenes and its Applications[Project]

KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker [Project]

Tracking Cars Using Optical Flow[Project]

Secrets of optical flow estimation and their principles[Project]

implmentation of the Black and Anandan dense optical flow method[Project]

Optical Flow Computation[Project]

Beyond Pixels: Exploring New Representations and Applications for Motion Analysis[Project]

A Database and Evaluation Methodology for Optical Flow[Project]

optical flow relative[Project]

Robust Optical Flow Estimation [Project]

optical flow[Project]

十七、图像检索Image Retrieval：

Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval [Paper][code]

十八、马尔科夫随机场Markov Random Fields：

Markov Random Fields for Super-Resolution [Project]

A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors [Project]

十九、运动检测Motion detection：

Moving Object Extraction, Using Models or Analysis of Regions [Project]

Background Subtraction: Experiments and Improvements for ViBe [Project]

A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications [Project]

changedetection.net: A new change detection benchmark dataset[Project]

ViBe - a powerful technique for background detection and subtraction in video sequences[Project]

Background Subtraction Program[Project]

Motion Detection Algorithms[Project]

Stuttgart Artificial Background Subtraction Dataset[Project]

Object Detection, Motion Estimation, and Tracking[Project]

Feature Detection and Description

General Libraries:

VLFeat –
Implementation of various feature descriptors (including SIFT, HOG, and LBP) and covariant feature detectors (including DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris). Easy-to-use Matlab interface. See Modern
features: Software – Slides providing a demonstration of VLFeat and also links to other software. Check also VLFeat
hands-on session training

OpenCV –
Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)

Fast Keypoint Detectors for Real-time Applications:

FAST –
High-speed corner detector implementation for a wide variety of platforms

AGAST –
Even faster than the FAST corner detector. A multi-scale version of this method is used for the BRISK descriptor (ECCV 2010).

Binary Descriptors for Real-Time Applications:

BRIEF –
C++ code for a fast and accurate interest point descriptor (not invariant to rotations and scale) (ECCV 2010)

ORB –
OpenCV implementation of the Oriented-Brief (ORB) descriptor (invariant to rotations, but not scale)

BRISK –
Efficient Binary descriptor invariant to rotations and scale. It includes a Matlab mex interface. (ICCV 2011)

FREAK –
Faster than BRISK (invariant to rotations and scale) (CVPR 2012)

SIFT and SURF Implementations:

SIFT: VLFeat, OpenCV, Original
code by David Lowe, GPU
implementation, OpenSIFT

SURF: Herbert
Bay’s code, OpenCV, GPU-SURF

Other Local Feature Detectors and Descriptors:

VGG
Affine Covariant features – Oxford code for various affine covariant feature detectors and descriptors.

LIOP
descriptor – Source code for the Local Intensity order Pattern (LIOP) descriptor (ICCV 2011).

Local
Symmetry Features – Source code for matching of local symmetry features under large variations in lighting, age, and rendering style (CVPR 2012).

Global Image Descriptors:

GIST –
Matlab code for the GIST descriptor

CENTRIST –
Global visual descriptor for scene categorization and object detection (PAMI 2011)

Feature Coding and Pooling

VGG
Feature Encoding Toolkit – Source code for various state-of-the-art feature encoding methods – including Standard hard encoding, Kernel codebook encoding, Locality-constrained linear encoding, and Fisher kernel encoding.

Spatial
Pyramid Matching – Source code for feature pooling based on spatial pyramid matching (widely used for image classification)

Convolutional Nets and Deep Learning

EBLearn –
C++ Library for Energy-Based Learning. It includes several demos and step-by-step instructions to train classifiers based on convolutional neural networks.

Torch7 –
Provides a matlab-like environment for state-of-the-art machine learning algorithms, including a fast implementation of convolutional neural networks.

Deep
Learning - Various links for deep learning software.

Part-Based Models

Deformable
Part-based Detector – Library provided by the authors of the original paper (state-of-the-art in PASCAL VOC detection task)

Efficient
Deformable Part-Based Detector – Branch-and-Bound implementation for a deformable part-based detector.

Accelerated
Deformable Part Model – Efficient implementation of a method that achieves the exact same performance of deformable part-based detectors but with significant acceleration (ECCV 2012).

Coarse-to-Fine
Deformable Part Model – Fast approach for deformable object detection (CVPR 2011).

Poselets –
C++ and Matlab versions for object detection based on poselets.

Part-based
Face Detector and Pose Estimation – Implementation of a unified approach for face detection, pose estimation, and landmark localization (CVPR 2012).

Attributes and Semantic Features

Relative
Attributes – Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).

Object
Bank – Implementation of object bank semantic features (NIPS 2010). See also ActionBank

Classemes,
Picodes, and Meta-class features – Software for extracting high-level image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).

Large-Scale Learning

Additive
Kernels – Source code for fast additive kernel SVM classifiers (PAMI 2013).

LIBLINEAR –
Library for large-scale linear SVM classification.

VLFeat –
Implementation for Pegasos SVM and Homogeneous Kernel map.

Fast Indexing and Image Retrieval

FLANN –
Library for performing fast approximate nearest neighbor.

Kernelized
LSH – Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).

ITQ
Binary codes – Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing (CVPR 2011).

INRIA
Image Retrieval – Efficient code for state-of-the-art large-scale image retrieval (CVPR 2011).

Object Detection

See Part-based
Models and Convolutional
Nets above.

Pedestrian
Detection at 100fps – Very fast and accurate pedestrian detector (CVPR 2012).

Caltech
Pedestrian Detection Benchmark – Excellent resource for pedestrian detection, with various links for state-of-the-art implementations.

OpenCV –
Enhanced implementation of Viola&Jones real-time object detector, with trained models for face detection.

Efficient
Subwindow Search – Source code for branch-and-bound optimization for efficient object localization (CVPR 2008).

3D Recognition

Point-Cloud
Library – Library for 3D image and point cloud processing.

Action Recognition

ActionBank –
Source code for action recognition based on the ActionBank representation (CVPR 2012).

STIP
Features – software for computing space-time interest point descriptors

Independent
Subspace Analysis – Look for Stacked ISA for Videos (CVPR 2011)

Velocity
Histories of Tracked Keypoints - C++ code for activity recognition using the velocity histories of tracked keypoints (ICCV 2009)

Datasets

Attributes

Animals
with Attributes – 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.

aYahoo
and aPascal – Attribute annotations for images collected from Yahoo and Pascal VOC 2008.

FaceTracer –
15,000 faces annotated with 10 attributes and fiducial points.

PubFig –
58,797 face images of 200 people with 73 attribute classifier outputs.

LFW –
13,233 face images of 5,749 people with 73 attribute classifier outputs.

Human
Attributes – 8,000 people with annotated attributes. Check also this link for
another dataset of human attributes.

SUN
Attribute Database – Large-scale scene attribute database with a taxonomy of 102 attributes.

ImageNet
Attributes – Variety of attribute labels for the ImageNet dataset.

Relative
attributes – Data for OSR and a subset of PubFig datasets. Check also this link for
the WhittleSearch data.

Attribute
Discovery Dataset – Images of shopping categories associated with textual descriptions.

Fine-grained Visual Categorization

Caltech-UCSD
Birds Dataset – Hundreds of bird categories with annotated parts and attributes.

Stanford
Dogs Dataset – 20,000 images of 120 breeds of dogs from around the world.

Oxford-IIIT
Pet Dataset – 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is included.

Leeds
Butterfly Dataset – 832 images of 10 species of butterflies.

Oxford
Flower Dataset – Hundreds of flower categories.

Face Detection

FDDB –
UMass face detection dataset and benchmark (5,000+ faces)

CMU/MIT –
Classical face detection dataset.

Face Recognition

Face
Recognition Homepage – Large collection of face recognition datasets.

LFW –
UMass unconstrained face recognition dataset (13,000+ face images).

NIST
Face Homepage – includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.

CMU
Multi-PIE – contains more than 750,000 images of 337 people, with 15 different views and 19 lighting conditions.

FERET –
Classical face recognition dataset.

Deng
Cai’s face dataset in Matlab Format – Easy to use if you want play with simple face datasets including Yale, ORL, PIE, and Extended Yale B.

SCFace –
Low-resolution face dataset captured from surveillance cameras.

Handwritten Digits

MNIST –
large dataset containing a training set of 60,000 examples, and a test set of 10,000 examples.

Pedestrian Detection

Caltech
Pedestrian Detection Benchmark – 10 hours of video taken from a vehicle,350K bounding boxes for about 2.3K unique pedestrians.

INRIA
Person Dataset – Currently one of the most popular pedestrian detection datasets.

ETH
Pedestrian Dataset – Urban dataset captured from a stereo rig mounted on a stroller.

TUD-Brussels
Pedestrian Dataset – Dataset with image pairs recorded in an crowded urban setting with an onboard camera.

PASCAL
Human Detection – One of 20 categories in PASCAL VOC detection challenges.

USC
Pedestrian Dataset – Small dataset captured from surveillance cameras.

Generic Object Recognition

ImageNet –
Currently the largest visual recognition dataset in terms of number of categories and images.

Tiny
Images – 80 million 32x32 low resolution images.

Pascal
VOC – One of the most influential visual recognition datasets.

Caltech
101 / Caltech
256 – Popular image datasets containing 101 and 256 object categories, respectively.

MIT
LabelMe – Online annotation tool for building computer vision databases.

Scene Recognition

MIT
SUN Dataset – MIT scene understanding dataset.

UIUC
Fifteen Scene Categories – Dataset of 15 natural scene categories.

Feature Detection and Description

VGG
Affine Dataset – Widely used dataset for measuring performance of feature detection and description. CheckVLBenchmarks for
an evaluation framework.

Action Recognition

Benchmarking
Activity Recognition – CVPR 2012 tutorial covering various datasets for action recognition.

RGBD Recognition

RGB-D
Object Dataset – Dataset containing 300 common household objects

Reference:

[1]: http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html

转自:http://xilinx.eetrend.com/article/8919