六、抠图Image
Matting

 rails页面中加入以下表单

澳门微尼斯人手机版 1

四、显著性检测Saliency
Detection:

rails g rails_kindeditor:install

rails kindeditor:assets

澳门微尼斯人手机版 2

Datasets

    js

 

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

创建配置文件,并且引入js

澳门微尼斯人手机版 3

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

 

澳门微尼斯人手机版 4

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

在gemfile中加入(后面版本别丢)

澳门微尼斯人手机版 5

Scene
Recognition

  <%= form_for @article do |f| %>
    <%= f.kindeditor :content, :editor_id => 'my_editor' %>
  <% end %>

澳门微尼斯人手机版 6

  • 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]

澳门微尼斯人手机版,  js获取编辑器的内容

批量修改文件名下载地址:

Reference:

  

1.软件基本使用

  • Nonparametric
    Scene Parsing via Label
    Transfer [Project]

  

也可以点击批量模板生成

三、目标检测Object
Detection:

gem 'rails_kindeditor', '~> 0.5.0'

澳门微尼斯人手机版 7

  • Kinect
    toolbox[Project]
  • OpenNI[Project]
  • zouxy09
    CSDN
    Blog[Resource]
  • FingerTracker
    手指跟踪[code]

   $ bundle  

点击连接/测试
看是否成功,同时选择要连接的数据库,不然加载全部库要等好久的

  • 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).
  my_editor.html();

可以对相应的字段修改,下面这个是自带的模板示例
可以照着这个去写自己业务逻辑

十五、场景解释:

参考原文:

  • 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).

对刚出社会的我来说可以说什么都不知道,对此赶紧学习了一下才发现这是李天平老师开发的软件膜拜一下!

十三、一些实用工具:

澳门微尼斯人手机版 8

十一、目标、行为识别Object,
Action Recognition:

澳门微尼斯人手机版 9

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

澳门微尼斯人手机版 10

  • 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.

然后再去点生成模板

Feature
Detection and Description

 

七、目标跟踪Object
Tracking:

学习使用呢,下载完成后有在左边模板管理有一个

Global Image
Descriptors: 

3.模板生成

  • 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]

以此总结一下

  • finger-detection-and-gesture-recognition [Code]
  • Hand and
    Finger Detection using
    JavaCV[Project]
  • Hand and
    fingers
    detection[Code]

 

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

前几天做项目用到了动软代码生成器澳门微尼斯人手机版 11

十二、图像处理:

 

  • 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)

我在百度下载的是V2.78版的

  • 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](]

添加服务器 选择要连接的数据库

  • SIFT: VLFeat, OpenCV, Original
    code by David Lowe, GPU
    implementation, OpenSIFT
  • SURF: Herbert
    Bay’s
    code, OpenCV, GPU-SURF

但有一个问题就是生成的文件名都是表名,如果表很多的话就要改很多,我们用生成器就是为了节约时间

八、Kinect:

为了解决这个问题我写了WindowsForms
可以批量修改生成文件的后缀名已达到项目的符合的命名规范

  • 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]

这里直接打开生成会报错

  • 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.

2.所有对象使用

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