Socio-mobile landmark recognition using local features with adaptive region selection
文献类型：期刊论文
| 作者 | Zhang, Chunjie1 ; Zhang, Yifan2; Zhu, Xiaobin3; Xue, Zhe1; Qin, Lei4; Huang, Qingming1,4; Tian, Qi5
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2016-01-08 |
| 卷号 | 172页码:100-113 |
| 关键词 | Mobile Social relationship Adaptive region selection Local feature Geo-codebook Visual recognition |
| 英文摘要 | With the fast development of mobile devices as well as the broadband wireless network, mobile devices are playing a more and more important role in people's daily life. Nowadays, many landmark images are captured by mobile devices. However, these images are often captured under different lightening conditions with varied poses and camera orientations. Besides, people are inherently connected by personal interests as well as various interactions. To alleviate the imaging problem with mobile devices as well as take advantage of the social information for mobile visual applications, we propose a novel socio-mobile visual recognition method using local features with adaptive region selection. We densely extract local regions and use the pixel gradients to represent each local region. Each local region is divided into 4 x 4 subregions to combine the spatial information. Instead of using fixed pixel numbers for each subregion, we adaptively choose the proper size of each subregion to cope with varied poses and camera orientations. The most discriminative local features are then chosen by minimizing the sparse coding loss. Besides, a geo-discriminative codebook is also generated to take advantages of images' location information. Moreover, we jointly consider the visual distances as well as user's friends' matching results to further boost the final visual recognition performance. We achieve the state-of-the-art performance on the Stanford mobile visual search dataset and the San Francisco landmark dataset. These experimental results demonstrate the effectiveness and efficiency of the proposed adaptive region selection based local features for sodo-mobile landmark recognition. (C) 2015 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | IMAGE CLASSIFICATION ; ANNOTATION ; SCALE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000364884700012 |
| 公开日期 | 2016-02-26 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10519]  |
| 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 |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Beijing Technol & Business Univ, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intell Info Proc, Beijing 100190, 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 | Zhang, Chunjie,Zhang, Yifan,Zhu, Xiaobin,et al. Socio-mobile landmark recognition using local features with adaptive region selection[J]. NEUROCOMPUTING,2016,172:100-113. |
| APA | Zhang, Chunjie.,Zhang, Yifan.,Zhu, Xiaobin.,Xue, Zhe.,Qin, Lei.,...&Tian, Qi.(2016).Socio-mobile landmark recognition using local features with adaptive region selection.NEUROCOMPUTING,172,100-113. |
| MLA | Zhang, Chunjie,et al."Socio-mobile landmark recognition using local features with adaptive region selection".NEUROCOMPUTING 172(2016):100-113. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。