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  • 2013计算机视觉代码合集

    申明:本文非原创,原文转载自:http://www.yuanyong.org/blog/cv/cv-code

    一、特征提取Feature Extraction

    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

    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]
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  • 原文地址:https://www.cnblogs.com/xwolfs/p/3945450.html
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