计算机视觉领域经典论文源码_计算机视觉经典源码

                                                                                      计算机视觉领域经典论文源码

计算机视觉领域最新论文的代码实现：https://github.com/kjw0612/awesome-deep-vision

另外一位大牛也是总结了很多方向的代码以及连接，可以参考他的博客：

https://blog.csdn.net/Ddreaming/article/details/52416643

另一博客整理的资源：
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
 

下面是另一博客整理的资源：

从cvchina搞到的机器视觉开源处理库汇总，转来了，很给力，还在不断更新。。。

通用库/General Library
OpenCV
无需多言。

RAVL
Recognition And Vision Library. 线程安全。强大的IO机制。包含AAM。

CImg
很酷的一个图像处理包。整个库只有一个头文件。包含一个基于PDE的光流算法。

图像，视频IO/Image, Video IO
FreeImage
DevIL
ImageMagick
FFMPEG
VideoInput
portVideo
AR相关/Augmented Reality
ARToolKit
基于Marker的AR库

ARToolKitPlus
ARToolKit的增强版。实现了更好的姿态估计算法。

PTAM
实时的跟踪、SLAM、AR库。无需Marker，模板，内置传感器等。

BazAR
基于特征点检测和识别的AR库。

局部不变特征/Local Invariant Feature
VLFeat
目前最好的Sift开源实现。同时包含了KD-tree，KD-Forest，BoW实现。

Ferns
基于Naive Bayesian Bundle的特征点识别。高速，但占用内存高。

SIFT By Rob Hess
基于OpenCV的Sift实现。

目标检测/Object Detection
AdaBoost By JianXin.Wu
又一个AdaBoost实现。训练速度快。

行人检测 By JianXin.Wu
基于Centrist和Linear SVM的快速行人检测。

（近似）最近邻/ANN
FLANN
目前最完整的（近似）最近邻开源库。不但实现了一系列查找算法，还包含了一种自动选取最快算法的机制。

ANN
另外一个近似最近邻库。

SLAM & SFM
SceneLib [LGPL]
monoSLAM库。由Androw Davison开发。

图像分割/Segmentation
SLIC Super Pixel
使用Simple Linear Iterative Clustering产生指定数目，近似均匀分布的Super Pixel。

目标跟踪/Tracking
TLD
基于Online Random Forest的目标跟踪算法。

KLT
Kanade-Lucas-Tracker

Online boosting trackers
Online Boosting Trackers

直线检测/Line Detection
DSCC
基于联通域连接的直线检测算法。

LSD [GPL]
基于梯度的，局部直线段检测算子。

指纹/Finger Print
pHash [GPL]
基于感知的多媒体文件Hash算法。（提取，对比图像、视频、音频的指纹）

视觉显著性/Visual Salience
Global Contrast Based Salient Region Detection
Ming-Ming Cheng的视觉显著性算法。

FFT/DWT
FFTW [GPL]
最快，最好的开源FFT。

FFTReal [WTFPL]
轻量级的FFT实现。许可证是亮点。

音频处理/Audio processing
STK [Free]
音频处理，音频合成。

libsndfile [LGPL]
音频文件IO。

libsamplerate [GPL ]
音频重采样。

小波变换

快速小波变换（FWT）

FWT
BRIEF: Binary Robust Independent Elementary Feature 一个很好的局部特征描述子，里面有FAST corner + BRIEF实现特征点匹配的DEMO：http://cvlab.epfl.ch/software/brief/

http://code.google.com/p/javacv

Java打包的OpenCV, FFmpeg, libdc1394, PGR FlyCapture, OpenKinect, videoInput, and ARToolKitPlus库。可以放在Android上用~

 

libHIK,HIK SVM，计算HIK SVM跟Centrist的Lib。http://c2inet.sce.ntu.edu.sg/Jianxin/projects/libHIK/libHIK.htm

 

一组视觉显著性检测代码的链接：http://cg.cs.tsinghua.edu.cn/people/~cmm/saliency/

三篇整理了很多特征、机器学习算法、计算机视觉和模式识别领域经典论文等源码资源的

博客：

1.http://www.cnblogs.com/ajian005/archive/2012/11/04/2841171.html

2.http://blog.csdn.net/yf0811240333/article/details/42076677

3.http://www.cnblogs.com/einyboy/p/3594432.html