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Coarse-to-Fine Description for Fine-Grained Visual Categorization

文献类型：期刊论文

作者Yao, Hantao1,2; Zhang, Shiliang3; Zhang, Yongdong1,4; Li, Jintao1; Tian, Qi5
刊名IEEE TRANSACTIONS ON IMAGE PROCESSING
出版日期2016-10-01
卷号25期号:10页码:4858-4872
ISSN号1057-7149
DOI10.1109/TIP.2016.2599102
英文摘要Recent years have witnessed the significant advance in fine-grained visual categorization, which targets to classify the objects belonging to the same species. To capture enough subtle visual differences and build discriminative visual description, most of the existing methods heavily rely on the artificial part annotations, which are expensive to collect in real applications. Motivated to conquer this issue, this paper proposes a multilevel coarse-to-fine object description. This novel description only requires the original image as input, but could automatically generate visual descriptions discriminative enough for fine-grained visual categorization. This description is extracted from five sources representing coarse-to-fine visual clues: 1) original image is used as the source of global visual clue; 2) object bounding boxes are generated using convolutional neural network (CNN); 3) with the generated bounding box, foreground is segmented using the proposed k nearest neighbour-based co-segmentation algorithm; and 4) two types of part segmentations are generated by dividing the foreground with an unsupervised part learning strategy. The final description is generated by feeding these sources into CNN models and concatenating their outputs. Experiments on two public benchmark data sets show the impressive performance of this coarse-to-fine description, i.e., classification accuracy achieves 82.5% on CUB-200-2011, and 86.9% on fine-grained visual categorization-Aircraft, respectively, which outperform many recent works.
资助项目National High Technology Research and Development Program of China[2014AA015202] ; National Nature Science Foundation of China[61525206] ; National Nature Science Foundation of China[61428207] ; National Nature Science Foundation of China[61572050] ; National Nature Science Foundation of China[91538111] ; National Nature Science Foundation of China[61429201] ; Beijing Advanced Innovation Center for Imaging Technology[BAICIT-2016009] ; ARO[W911NF-15-1-0290] ; Faculty Research Gift Awards by NEC Laboratories of America ; Blippar
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000382677700009
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/8063]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhang, Yongdong
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
4.Capital Normal Univ, Beijing Adv Innovat Ctr Imaging Technol, Beijing 100048, Peoples R China
5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
推荐引用方式
GB/T 7714		 Yao, Hantao,Zhang, Shiliang,Zhang, Yongdong,et al. Coarse-to-Fine Description for Fine-Grained Visual Categorization[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2016,25(10):4858-4872.
APA Yao, Hantao,Zhang, Shiliang,Zhang, Yongdong,Li, Jintao,&Tian, Qi.(2016).Coarse-to-Fine Description for Fine-Grained Visual Categorization.IEEE TRANSACTIONS ON IMAGE PROCESSING,25(10),4858-4872.
MLA Yao, Hantao,et al."Coarse-to-Fine Description for Fine-Grained Visual Categorization".IEEE TRANSACTIONS ON IMAGE PROCESSING 25.10(2016):4858-4872.

入库方式： OAI收割

来源：计算技术研究所

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