Depth Information Guided Crowd Counting for complex crowd scenes
文献类型：期刊论文
| 作者 | Xu, Mingliang1; Ge, Zhaoyang1; Jiang, Xiaoheng1; Cui, Gaoge1; Lv, Pei1; Zhou, Bing1; Xu, Changsheng2
|
| 刊名 | PATTERN RECOGNITION LETTERS
 |
| 出版日期 | 2019-07-01 |
| 卷号 | 125页码:563-569 |
| 关键词 | Crowd counting Depth information Pedestrian detection Density estimation |
| ISSN号 | 0167-8655 |
| DOI | 10.1016/j.patrec.2019.02.026 |
| 通讯作者 | Jiang, Xiaoheng(jiangxiaoheng@zzu.edu.cn) |
| 英文摘要 | It is important to monitor and analyze crowd events for the sake of city safety. In an EDOF (extended depth of field) image with a crowded scene, the distribution of people is highly imbalanced. People far away from the camera look much smaller and often occlude each other heavily, while people close to the camera look larger. In such a case, it is difficult to accurately estimate the number of people by using one technique. In this paper, we propose a Depth Information Guided Crowd Counting (DigCrowd) method to deal with crowded EDOF scenes. DigCrowd first uses the depth information of an image to segment the scene into a far-view region and a near-view region. Then Digcrowd maps the far-view region to its crowd density map and uses a detection method to count the people in the near-view region. In addition, we introduce a new crowd dataset that contains 10 0 0 images. Experimental results demonstrate the effectiveness of our DigCrowd method. (C) 2019 Elsevier B.V. All rights reserved. |
| WOS关键词 | PEDESTRIAN DETECTION ; CLASSIFICATION |
| 资助项目 | National Natural Science Foundation of China[61802351] ; National Natural Science Foundation of China[61822701] ; National Natural Science Foundation of China[61672469] ; National Natural Science Foundation of China[61602420] ; China Postdoctoral Science Foundation[2018M632802] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000482374500077 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27339]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 通讯作者 | Jiang, Xiaoheng |
| 作者单位 | 1.Zhengzhou Univ, 100 Sci Ave, Zhengzhou 450000, Henan, Peoples R China 2.Chinese Acad Sci, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Mingliang,Ge, Zhaoyang,Jiang, Xiaoheng,et al. Depth Information Guided Crowd Counting for complex crowd scenes[J]. PATTERN RECOGNITION LETTERS,2019,125:563-569. |
| APA | Xu, Mingliang.,Ge, Zhaoyang.,Jiang, Xiaoheng.,Cui, Gaoge.,Lv, Pei.,...&Xu, Changsheng.(2019).Depth Information Guided Crowd Counting for complex crowd scenes.PATTERN RECOGNITION LETTERS,125,563-569. |
| MLA | Xu, Mingliang,et al."Depth Information Guided Crowd Counting for complex crowd scenes".PATTERN RECOGNITION LETTERS 125(2019):563-569. |
入库方式： OAI收割
来源：自动化研究所
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