| 用于图像场景分类的空间视觉词袋模型 |
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| 引用本文： | 王宇新,郭禾,何昌钦,冯振,贾棋.用于图像场景分类的空间视觉词袋模型[J].计算机科学,2011,38(8):265-268. |
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| 作者姓名： | 王宇新 郭禾 何昌钦 冯振 贾棋 |
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| 作者单位： | (大连理工大学计算机科学与技术学院 大连116023);(大连理工大学软件学院 大连116620) |
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| 摘 要： | 以传统的词袋模型为基础,根据同类场景图像具有空间相似性的特点,提出了一种用于图像场景分类的空间视觉词袋模型.首先将图像进行不同等级的空间划分,针对对应空问子区域进行特征提取和k均值聚类,形成该区域的视觉关键词,进而构建整个训练图像集的空间视觉词典.进行场景识别时,将所有空间子区域的视觉关键词连接成一个全局特征向量进行相...
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| 关 键 词： | 场景分类 词袋 空间聚类 空间视觉词典 支持向量机 |
Bag of Spatial Visual Words Model for Scene Classification |
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| WANG Yu-xin,GUO He,HE Chang-qin,FENG Zhen,JIA Qi.Bag of Spatial Visual Words Model for Scene Classification[J].Computer Science,2011,38(8):265-268. |
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| Authors: | WANG Yu-xin GUO He HE Chang-qin FENG Zhen JIA Qi |
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| Affiliation: | (School of Computer Science and Technology,Dalian University of Technology,Dalian 116023,China);(School of Software,Dalian University of Technology,Dalian 116620,China) |
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| Abstract: | An approach to recognize scene categories by means of a novel model named bag of spatial visual words was proposed. Images were hierarchically divided into sub regions and the spatial visual vocabulary was constructed by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions were concatenated to form a global feature vector.The classification result was obtained using LIBSVM and two kinds of features were used in the experiments:"V1-like" filters and PACK features. |
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| Keywords: | Scene classification Bag of words Spatial clustering Spatial visual vocabulary SVM |
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