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Description: 自李菲菲提出bag of words 这个想法以来，借助于该思路的各种算法层出不穷，也表现非常不错的性能。该文件是在其人的tutorial上提供的一个Demo，有非常详细的注释，希望能给大家带来帮助-Since the LI Fei-made bag of words this idea since the idea of the various algorithms by means of an endless stream, but also doing a very good performance. This file is in its people' s tutorial available on a Demo, with very detailed notes, want to give us some help
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Author: 张俊格 |
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Description: bag of words 图像识别算法，斯坦福大学李飞飞实验室做的demo-bag of words
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Author: 李桃 |
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Description: bag-of-words by R. Fergus, L. Fei-Fei and A. Torralba
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Author: luwenhao |
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Description: Bag of Words source code
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Author: shizhi |
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Description: Realization of Bag Of Words frames segmentation see http://www.vlfeat.org/applications/apps.html#apps.caltech-101
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Author: svamoscow |
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Description: 基于bag of visual words 模型的人脸二分类代码，使用plsa等两种模式进行分类-Bag of visual words ,face recognition ,plsa
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Author: ryetal |
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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: matlab编写的bag of words，可以对目标进行特征提取，实现目标匹配识别。-Matlab prepared bag of words, the target feature extraction, to achieve the goal of matching recognition.
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Author: 色楞格 |
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Description: NLP-Reduce is a natural language query interface that allows its users to enter full English questions, sentence fragments, and keywords. It processes queries a s bag of words and only employs a reduced set of natural language processing techniques, such as stemming and synonym expansion. Dependencies between word or phrases in the queries are only identified by the relationships that exit between the elements in a queries knowledge base. This weakness is also its major strength, as it is completely portable and robust to ungrammatical or deficient input. -NLP-Reduce is a natural language query interface that allows its users to enter full English questions, sentence fragments, and keywords. It processes queries a s bag of words and only employs a reduced set of natural language processing techniques, such as stemming and synonym expansion. Dependencies between word or phrases in the queries are only identified by the relationships that exit between the elements in a queries knowledge base. This weakness is also its major strength, as it is completely portable and robust to ungrammatical or deficient input.
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Author: Daniella |
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Description: Bag of Words is an implementation of feature extraction in Matlab
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Author: johnaros |
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Description: 游戏分析，包含使用说明和源码结构分析，可成功运行。-Bag of words source code analysis
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Author: 张大山 |
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Description: Content-Based Image Retrieval using the Bag-of-Words Concept
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Author: balaram |
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Description: Bag of words approaches
Parts and structure approaches
Discriminative methods
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Author: Sam |
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Description: Realization of Bag Of Words frames segmentation see http://www.vlfeat.org/applications/apps.html#apps.caltech-101
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Size: 182272 |
Author: 凝聚了 |
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Description: bog of words(BOW)用于图像特征描述-bog of words(BOW)
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Author: 素联 |
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Description: 图像特征点提取词袋模型,添加LBP特征的选择，融合两种特征进行图像的特征提取-bag of words in images
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Author: ningning |
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Description: 将每一张图的特征点采样聚类成图片的视觉单词 即视觉单词,就是对应图片的代表 创建数据库,将每张图片的视觉单词入库,并建立索引-Will feature a map of each sampling point clustered into visual images of words that is visual words, is to represent the corresponding picture of the is created, the visual image of each word storage and indexing
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Author: 耿文浩 |
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Description: 利用词袋模型，实现对Merchdata数据库内图像的标注功能。使用了bagoffeatures库函数。(The bag-of-words model is used to implement the annotation of images in the Merchdata database. Use the bagoffeatures library function.)
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Author: 过了就好 |
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