Geolocalized Modeling for Dish Recognition
文献类型：期刊论文
| 作者 | Xu, Ruihan1; Herranz, Luis1; Jiang, Shuqiang1; Wang, Shuang1; Song, Xinhang1; Jain, Ramesh2 |
| 刊名 | IEEE TRANSACTIONS ON MULTIMEDIA
 |
| 出版日期 | 2015-08-01 |
| 卷号 | 17期号:8页码:1187-1199 |
| 关键词 | Food recognition geolocation image tagging mobile applications |
| ISSN号 | 1520-9210 |
| DOI | 10.1109/TMM.2015.2438717 |
| 英文摘要 | Food-related photos have become increasingly popular, due to social networks, food recommendations, and dietary assessment systems. Reliable annotation is essential in those systems, but unconstrained automatic food recognition is still not accurate enough. Most works focus on exploiting only the visual content while ignoring the context. To address this limitation, in this paper we explore leveraging geolocation and external information about restaurants to simplify the classification problem. We propose a framework incorporating discriminative classification in geolocalized settings and introduce the concept of geolocalized models, which, in our scenario, are trained locally at each restaurant location. In particular, we propose two strategies to implement this framework: geolocalized voting and combinations of bundled classifiers. Both models show promising performance, and the later is particularly efficient and scalable. We collected a restaurant-oriented food dataset with food images, dish tags, and restaurant-level information, such as the menu and geolocation. Experiments on this dataset show that exploiting geolocation improves around 30% the recognition performance, and geolocalized models contribute with an additional 3-8% absolute gain, while they can be trained up to five times faster. |
| 资助项目 | National Basic Research Program of China (973 Program)[2012CB316400] ; National Natural Science Foundation of China[61322212] ; National Natural Science Foundation of China[61450110446] ; National Hi-Tech Development Program (863 Program) of China[2014AA015202] ; CAS President's International Fellowship Initiative[2011Y1GB05] ; Lenovo Outstanding Young Scientists Program |
| WOS研究方向 | Computer Science ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000358233000006 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/9598]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Xu, Ruihan |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Calif Irvine, Irvine, CA 92697 USA |
| 推荐引用方式 GB/T 7714 | Xu, Ruihan,Herranz, Luis,Jiang, Shuqiang,et al. Geolocalized Modeling for Dish Recognition[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2015,17(8):1187-1199. |
| APA | Xu, Ruihan,Herranz, Luis,Jiang, Shuqiang,Wang, Shuang,Song, Xinhang,&Jain, Ramesh.(2015).Geolocalized Modeling for Dish Recognition.IEEE TRANSACTIONS ON MULTIMEDIA,17(8),1187-1199. |
| MLA | Xu, Ruihan,et al."Geolocalized Modeling for Dish Recognition".IEEE TRANSACTIONS ON MULTIMEDIA 17.8(2015):1187-1199. |
入库方式： OAI收割
来源：计算技术研究所
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