| High-Order Topology Modeling of Visual Words for Image Classification | |
Huang, Kaiqi1 ; Wang, Chong1; Tao, Dacheng2
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| 发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 2015-11-01 | |
| 卷号 | 24期号:11页码:3598 - 3608 |
| 文章类型 | Article |
| 摘要 | Modeling relationship between visual words in feature encoding is important in image classification. Recent methods consider this relationship in either image or feature space, and most of them incorporate only pairwise relationship (between visual words). However, in situations involving large variability in images, one cannot capture intrinsic invariance of intra-class images using low-order pairwise relationship. The result is not robust to larger variations in images. In addition, as the number of potential pairings grows exponentially with the number of visual words, the task of learning becomes computationally expensive. To overcome these two limitations, we propose an efficient classification framework that exploits high-order topology of visual words in the feature space, as follows. First, we propose a search algorithm that seeks dependence between the visual words. This dependence is used to construct higher order topology in the feature space. Then, the local features are encoded according to this higher order topology to improve the image classification. Experiments involving four common data sets, namely PASCAL VOC 2007, 15 Scenes, Caltech 101, and UIUC Sport Event, demonstrate that the dependence search significantly improves the efficiency of higher order topological construction, and consequently increases the image classification in all these data sets. |
| 关键词 | Image Classification Feature Encoding Visual Words Higher-order |
| WOS标题词 | Science & Technology ; Technology |
| 关键词[WOS] | SELECTION |
| URL | 查看原文 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000358247700006 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/8884 |
| 专题 | 智能感知与计算研究中心 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia |
| 第一作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Huang, Kaiqi,Wang, Chong,Tao, Dacheng. High-Order Topology Modeling of Visual Words for Image Classification[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(11):3598 - 3608. |
| APA | Huang, Kaiqi,Wang, Chong,&Tao, Dacheng.(2015).High-Order Topology Modeling of Visual Words for Image Classification.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(11),3598 - 3608. |
| MLA | Huang, Kaiqi,et al."High-Order Topology Modeling of Visual Words for Image Classification".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.11(2015):3598 - 3608. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Kaiqi Huang_High-Ord（1884KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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