CASIA OpenIR  > 类脑智能研究中心
Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance
Zhaoxiang Zhang; Min Li
2012-05-02
发表期刊Optical Engineering
卷号51期号:4页码:1-14
摘要Crowd density estimation in public areas with people gathering and waiting has been a challenging problem for visual surveillance over many years. Tiny motions, like when people turn around, wander about, and turn their heads, happen randomly now and then in crowds, which makes it difficult to achieve high-performance crowd density estimation based on traditional foreground detection. A novel accumulated mosaic image difference feature is proposed to represent these complicated random motion patterns for accurate foreground detection. The obtained foreground is then normalized based on the perspective distortion correction model to achieve a reasonable crowd density measurement for observed areas. Numerous experiments are conducted in different scenes of various view angles, and experimental results demonstrate the effectiveness and robustness of our proposed method.
关键词Distortion Image Segmentation Statistical Analysis Surveillance Video
WOS记录号WOS:000304015100065
引用统计
被引频次:1[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/173211/13205
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
GB/T 7714
Zhaoxiang Zhang,Min Li. Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance[J]. Optical Engineering,2012,51(4):1-14.
APA Zhaoxiang Zhang,&Min Li.(2012).Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance.Optical Engineering,51(4),1-14.
MLA Zhaoxiang Zhang,et al."Crowd density estimation based on statistical analysis of local intra-crowd motions for public area surveillance".Optical Engineering 51.4(2012):1-14.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhaoxiang Zhang]的文章
[Min Li]的文章
百度学术
百度学术中相似的文章
[Zhaoxiang Zhang]的文章
[Min Li]的文章
必应学术
必应学术中相似的文章
[Zhaoxiang Zhang]的文章
[Min Li]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

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。