Multi-view pedestrian captioning with an attention topic CNN model
文献类型：期刊论文
| 作者 | Liu, Quan1,2,4; Chen, Yingying3,4 ; Wang, Jinqiao3,4; Zhang, Sijiong1,2,4
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| 刊名 | COMPUTERS IN INDUSTRY
 |
| 出版日期 | 2018-05-01 |
| 卷号 | 97页码:47-53 |
| 关键词 | Image captioning Pedestrian description Multi-view captions |
| ISSN号 | 0166-3615 |
| DOI | 10.1016/j.compind.2018.01.015 |
| 通讯作者 | Liu, Quan(quanliu@niaot.ac.cn) |
| 英文摘要 | Image captioning is a fundamental task connecting computer vision and natural language processing. Recent researches usually concentrate on generic image captioning or video captioning among thousands of classes. However, they fail to cover detailed semantics and cannot effectively deal with a specific class of objects, such as pedestrian. Pedestrian captioning plays a critical role for analysis, identification and retrieval in massive collections of video data. Therefore, in this paper, we propose a novel approach to generate multi-view captions for pedestrian images with a topic attention mechanism on global and local semantic regions. Firstly, we detect different local parts of pedestrian and utilize a deep convolutional neural network (CNN) to extract a series of features from these local regions and the whole image. Then, we aggregate these features with a topic attention CNN model to produce a representative vector richly expressing the image from a different view at each time step. This feature vector is taken as input to a hierarchical recurrent neural network to generate multi-view captions for pedestrian images. Finally, a new dataset named CASIA_Pedestrian including 5000 pedestrian images and sentences pairs is collected to evaluate the performance of pedestrian captioning. Experiments and comparison results show the superiority of our proposed approach. (C) 2018 Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[61772527] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000432504700006 |
| 出版者 | ELSEVIER SCIENCE BV |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/28178]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 通讯作者 | Liu, Quan |
| 作者单位 | 1.Chinese Acad Sci, Nanjing Inst Astron Opt & Technol, Key Lab Astron Opt & Technol, Nanjing 210042, Jiangsu, Peoples R China 2.Chinese Acad Sci, Nanjing Inst Astron Opt & Technol, Natl Astron Observ, Nanjing 210042, Jiangsu, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Quan,Chen, Yingying,Wang, Jinqiao,et al. Multi-view pedestrian captioning with an attention topic CNN model[J]. COMPUTERS IN INDUSTRY,2018,97:47-53. |
| APA | Liu, Quan,Chen, Yingying,Wang, Jinqiao,&Zhang, Sijiong.(2018).Multi-view pedestrian captioning with an attention topic CNN model.COMPUTERS IN INDUSTRY,97,47-53. |
| MLA | Liu, Quan,et al."Multi-view pedestrian captioning with an attention topic CNN model".COMPUTERS IN INDUSTRY 97(2018):47-53. |
入库方式： OAI收割
来源：自动化研究所
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