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bag_words_demo
- 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
bag-of-words
- bag-of-words by R. Fergus, L. Fei-Fei and A. Torralba
caltech-image-search-1.0
- 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: Sc
wenzi_hanzi_yanzhengma-rerecognition
- 字母、文字、验证码识别程序，采用visual basic语言，初步实现了识别功能。-Letters, words, verification code identification procedures, using visual basic language, initially achieved recognition.
tetinex
- Retinex是由两个英文单词retina(视网膜)和cortex(皮层)组合而成，揭示了这一理论涉及模拟人类视觉系统的感知和理解过程。1963年Land首次提出了基于颜色恒常性的计算理论—— Retinex 理论，作为人类视觉对亮度和颜色感知的模型-Retinex is composed of two English words (retinal) and retina cortex (cortical) combination, reveals this theory to simulate
Bag-of-visual-words
- 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.
rough-set
- 图像场景分类中视觉词包分类的应用与操作代码-Review of the bag-of-visual-words models in image scene classification
image_processing3
- 图像工程作业3：基于视词袋模型的场景识别 (Scene recognition with bag of words)-Image Engineering Job 3: Scene Recognition Based visual bag of words (Scene recognition with bag of words)
Bag-of-visual-words
- 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 eac
BoV
- 一种场景分类的介绍，利用的是bag of visual words思想。-Introduction of a classification, using bag of visual words.
image_bliss
- Image Category Recognition using Bag of Visual Words Representation