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Description: 本程序是VC+MO的一个简单例子,对于初学GIS的朋友能起到抛砖引玉的作用!
MapObjects是建立在微软的对象链接和嵌入（OLE）2.0基础之上的。OLE是当今得到最广泛支持的面向目标的软件集成技术。用户像用砖块盖房子一样利用OLE组件开发和集成Windows应用。一个OLE控件是一个可重复使用的软件组件。OLE控件可以将许多其他OLE对象包装在一个包中。这个包可以反映某些特定的功能，如统计图和多媒体等，并可以直接嵌入支持OLE的应用中。OLE对象具有特征和方法，可以通过对它们的编程来控制对象的外观、行为以及相互作用。MapObjects是一个提供制图与GIS功能的OLE控件，它包含了超过45个可编程OLE对象。MapObjects地图控件可以直接插入到许多标准开发环境的工具集中，可以通过属性页操纵地图。这些属性页是在诸如VC之类的开发环境中建立的，或者通过其他程序化相关对象来控制地图。这些对象为应用开发人员提供了有力的制图与GIS功能支持。
-this procedure MO VC is a simple example. For novice GIS friends will play the role of something! MapObjects is built on Microsoft's Object Linking and Embedding (OLE) 2.0 foundation. OLE is currently the most widely supported goal-oriented software integration technology. Users like a brick house built like using OLE component development and integration Windows applications. An OLE is a reusable software components. OLE can be many other OLE objects packed in a bag. The package will reflect certain specific functions, such as charts and multimedia. and can directly support OLE embedded applications. OLE object with features and methods, through their control of programming targeted to the appearance, behavior and interaction. MapObjects is a provider of mapping and GIS functions of O
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Author: qianyou |
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Description: 快速高效的图像分类器，
Bag of features:
A simple bag of features classifier.
作者:Andrea Vedaldi
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Size: 20396 |
Author: 罗彤 |
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Description: 本程序是VC+MO的一个简单例子,对于初学GIS的朋友能起到抛砖引玉的作用!
MapObjects是建立在微软的对象链接和嵌入（OLE）2.0基础之上的。OLE是当今得到最广泛支持的面向目标的软件集成技术。用户像用砖块盖房子一样利用OLE组件开发和集成Windows应用。一个OLE控件是一个可重复使用的软件组件。OLE控件可以将许多其他OLE对象包装在一个包中。这个包可以反映某些特定的功能，如统计图和多媒体等，并可以直接嵌入支持OLE的应用中。OLE对象具有特征和方法，可以通过对它们的编程来控制对象的外观、行为以及相互作用。MapObjects是一个提供制图与GIS功能的OLE控件，它包含了超过45个可编程OLE对象。MapObjects地图控件可以直接插入到许多标准开发环境的工具集中，可以通过属性页操纵地图。这些属性页是在诸如VC之类的开发环境中建立的，或者通过其他程序化相关对象来控制地图。这些对象为应用开发人员提供了有力的制图与GIS功能支持。
-this procedure MO VC is a simple example. For novice GIS friends will play the role of something! MapObjects is built on Microsoft's Object Linking and Embedding (OLE) 2.0 foundation. OLE is currently the most widely supported goal-oriented software integration technology. Users like a brick house built like using OLE component development and integration Windows applications. An OLE is a reusable software components. OLE can be many other OLE objects packed in a bag. The package will reflect certain specific functions, such as charts and multimedia. and can directly support OLE embedded applications. OLE object with features and methods, through their control of programming targeted to the appearance, behavior and interaction. MapObjects is a provider of mapping and GIS functions of O
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Size: 231424 |
Author: qianyou |
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Description: 快速高效的图像分类器，
Bag of features:
A simple bag of features classifier.
作者:Andrea Vedaldi -Fast and efficient image classifier, Bag of features: A simple bag of features classifier. Author: Andrea Vedaldi
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Author: 罗彤 |
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Description: 本系统是基于Struts+Hibernate开发的一套后台管理系统，功能包含完善的权限管理，和信息发布功能。开发环境：Eclipse3.01+myeclipse3.84+mysql5.0(oracle、ms sqlserver2000)。
压缩包里包含了所有的组件、源码和SQL脚本以及工程文件。
这个系统也是花了点时间和精力才做好的，现在把源码给大家分享，欢迎大家进行交流，如果要用于商业用途，要打声招呼哦！！！
mysql初始数据库用户名:root,密码:1234
其它数据库请相应修改hibernate.cfg.xml这映射文件为与你数据库相匹配-The system is based on the Struts+ Hibernate to develop a set of background management system, features include a comprehensive rights management, and information dissemination functions. Development Environment: Eclipse3.01+ Myeclipse3.84+ Mysql5.0 (oracle, ms sqlserver2000). Compression bag that contains all the components, source code and SQL scripts, as well as engineering documents. The system also has spent time and energy to do a good job before, but now the source code to share with you, welcome to exchange, if to be used for commercial purposes, fight, oh say hello! ! ! initial mysql database username: root, Password: 1234 consequential amendments to other databases, please hibernate.cfg.xml mapping file for this database to match with you
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Author: leeawan |
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Description: Famous Bag of features PPTs-著名的Bag of features PPT
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Author: Conan |
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Description: Bag-of-Features匹配增加了空间位置信息-Bag-of-Features with spatial location information
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Author: lipeng |
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Description: 图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。
其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？
用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。
在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。-Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set.
In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem?
After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified.
Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram
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Author: lipiji |
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Description: 大规模图像检索的代码，matlab与c++混合编程。总结了目前图像检索领域目前主要存在的方法。通过阅读该代码，可以对于经典的“词袋”模型（bow模型）有个具体的了解，但是该代码没有提供前序的特征提取，是直接从对提取好的特征向量聚类开始的，包括了k-means，分层k-means（HKM）聚类，倒排文件的建立和索引等，该代码还提供了局部敏感哈希（LSH）方法。最后，这份代码是下面这篇论文的作者提供的，
Indexing in Large Scale Image Collections: Scaling Properties and Benchmark-This C++/Matlab package implements several algorithms used for large scale
image search. The algorithms are implemented in C++, with an eye on large
scale databases. It can handle millions of images and hundreds of millions
of local features. It has MEX interfaces for Matlab, but can also be used
(with possible future modifications) from Python and directly from C++. It
can also be used for approximate nearest neighbor search, especially using
the Kd-Trees or LSH implementations.
The algorithms can be divided into two broad categories, depending on the
approach taken for image search:
1. Bag of Words:
----------------
The images are represented by histograms of visual words.
It includes algorithms for computing dictionaries:
* K-Means.
* Approximate K-Means (AKM).
* Hierarchical K-Means (HKM).
It also includes algorithms for fast search:
* Inverted File Index.
* Inverted File Index with Extra Information (for example for implementing
Hamming Embedding).
*
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Author: 薛振华 |
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Description: 该论文在知网上付费下载，为2011年9月最新的关于Bag of Wo rds 算法的框架和基本内容，是学习bag of words算法的很好的入门参考。Bag of Words 算法是一种有效的基于语义特征提取与表达的物体识别算法, 算法充分学习文本检索算法的优点, 将图片整理为一系列视觉词汇的集合, 提取物体的语义特征, 实现感兴趣物体的有效检测与识别。-Bag of Word algo rithm is an efficient object r eco gnition alg or ithm based o n semantic features ex traction and
ex pression. It learns the v irt ues o f the text based sear ch alg or ithm to make imag es a r ang o f v isua l w o rds, ex tract the seman
t ic char acter s and carr y out the detectio n and recog nit ion o f inter est ing objects. This paper mainly discusses the frame and
basic content of Bag of Wor ds algo rithm.
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Author: Jessicaying |
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Description: Bag of Wo rds 算法是一种有效的基于语义特征提取与表达的物体识别算法, 算法充分学习文本检索算法的优
点, 将图片整理为一系列视觉词汇的集合, 提取物体的语义特征, 实现感兴趣物体的有效检测与识别。文章主要研究了Bag
of Wo rds 算法的框架和基本内容。-Bag of Wo in rds algorithm is an effective semantic features extracted and the expression of object recognition algorithm, the algorithm is fully learn the advantages of text retrieval algorithms
Points, pictures, order the collection of a series of visual vocabulary, extract the semantic features of objects to achieve the effective detection and identification of objects of interest. The article is mainly a Bag
framework and basic contents of the Wo in rds algorithm.
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Author: 张 |
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Description: 本程序针对光照变化和部分遮挡这两种情形,提出一种基于多帧视频图像的高稳定特征的交通标志识别方法。利用有交通标志的多帧视频图像的SURF特征建立bag of SURFs特征向量集,非常有利于对SURF研究的学者和研发人员进行学习和改造。-The program for the illumination changes and partial occlusion both cases, the paper proposes a high-stability characteristics of multi-frame video images of traffic sign recognition. There are traffic signs use SURF features multi-frame video images to establish bag of SURFs feature vector set, very beneficial for scholars and researchers to learn SURF research and transformation.
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Author: 刘恋 |
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Description: SIFT等局部特征的词袋模型实现。包括K-means聚类，直方图特征的形成，以及KNN分类。-SIFT local features such as word bag model implementation. Including K-means clustering to form histogram features, and KNN classification.
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Author: 张志智 |
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Description: Source Code for bag of features, developed in Matlab
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Author: lourdes |
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Description: Bag of features source code developed in matlab. It contains mex files for clustering and eucledian distance.
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Author: lourdes |
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Description: RubyGems是一个方便而强大的Ruby程序包管理器（ package manager），类似RedHat的RPM.它将一个Ruby应用程序打包到一个gem里，作为一个安装单元。 特点： 能远程安装包 包之间依赖关系的管理 简单可靠的卸载（uninstallation） 查询机制，能查询本地和远程服务器的包信息 能保持一个包的不同版本 基于Web的查看接口，能查看你安装的gem的信息。-RubyGems is a convenient and powerful Ruby program package manager (manager package), similar to the RPM. RedHat it will be a Ruby application packaged into a gem, as an installation unit. Features: remote installation package between the dependent relationship management simple and reliable unloading (uninstallation) query mechanism, can query packet of local and remote server can keep a bag of different versions based on Web view interface that can view the information you install the gem.
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Author: zzpudn56 |
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Description: This program gives a program which follows the naive bayes classifier to classify the processed reviews.This used in sentiment classification.n document classification, a bag of words is a sparse vector of occurrence counts of words that is, a sparse histogram over the vocabulary. In computer vision, a bag of visual words is a vector of occurrence counts of a vocabulary of local image features.-This program gives a program which follows the naive bayes classifier to classify the processed reviews.This used in sentiment classification.n document classification, a bag of words is a sparse vector of occurrence counts of words that is, a sparse histogram over the vocabulary. In computer vision, a bag of visual words is a vector of occurrence counts of a vocabulary of local image features.
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Author: Nivedha |
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Description: Generate bag of words features
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Author: taatyaa |
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Description: BAG OF WORDS算法应用于图片分类。图像特征用sift算法描述，分类机利用了libsvm方法。-BAG OF WORDS algorithm is applied to image classification. Image features using sift algorithm description, classification machine utilizes libsvm method.
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Author: zhouduo JSGIGBE |
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Description: 种基于期望最大化( E M) 算法的局部图像特征的语义提取方法。首先提取图像的局部图像特 征， 统计特征在视觉词汇本中的出现频率， 将图像表示成词袋模型； 引入文本分析中的潜在语义分析技术建立从低层图像 特征到高层图像语义之间的映射模型； 然后利用 E M 算法拟合概率模型， 得到图像局部特征的潜在语义概率分布； 最后利 用该模型提取出的图像在潜在语义上的分布来进行图像分析和理解。-Semantic extraction of local image features based on expectation maximization (E M) algorithm. First extract the local features of the image, the visual vocabulary in the frequency of statistical feature, the image into the bag of words model introduce the latent semantic analysis of the text the technology to establish the mapping model between image low-level features to high-level semantic image and then use the E M algorithm for fitting probability model, probabilistic latent semantic distribution of local image features the distribution of the final image by using the model extracted in the latent semantic of image analysis and understanding.
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Author: 杨雪 |
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