Depth Information Guided Crowd Counting for complex crowd scenes

doi:10.1016/j.patrec.2019.02.026

	Depth Information Guided Crowd Counting for complex crowd scenes
	Xu, Mingliang 1; Ge, Zhaoyang 1; Jiang, Xiaoheng 1; Cui, Gaoge 1; Lv, Pei 1; Zhou, Bing 1; Xu, Changsheng2
发表期刊	PATTERN RECOGNITION LETTERS
ISSN	0167-8655
	2019-07-01
卷号	125 页码:563-569
通讯作者	Jiang, Xiaoheng(jiangxiaoheng@zzu.edu.cn)
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.
关键词	Crowd counting Depth information Pedestrian detection Density estimation
DOI	10.1016/j.patrec.2019.02.026
关键词[WOS]	PEDESTRIAN DETECTION ; CLASSIFICATION
收录类别	SCI
语种	英语
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] ; 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]
项目资助者	National Natural Science Foundation of China ; China Postdoctoral Science Foundation
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000482374500077
出版者	ELSEVIER
引用统计	被引频次：35[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/27340
专题	多模态人工智能系统全国重点实验室_多媒体计算
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.