Fast Algorithm for Moving Target Detection

被引：0

作者：

Chen, Jian ^{[1
]}

Mei, Feng ^{[1
]}

Ye, Weijing ^{[1
]}

Wang, Hongkai ^{[1
]}

Shen, Xiaojun ^{[1
]}

Yao, Yiyang ^{[1
]}

机构：

[1] State Grid Zhejiang Elect Power Co, Informat & Telecommun Branch, Hangzhou 310007, Zhejiang, Peoples R China

来源：

PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年

关键词：

Moving Target Detection; Model Learning; Video Surveillance;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a moving target detection algorithm which combines background estimation and BING (Binarized Normed Gradients) Objectness is proposed in video surveillance. A simple background estimation method is used to detect a set of rough moving foreground in image, objectness detection within the foreground set will estimate another set of candidate object windows, and the target (pedestrians/vehicles) region by the intersection of areas derives from the former two steps. Besides, time cost is reduced by the decrease of estimation regions. Experiments on the outdoor datasets show that the combined method can not only achieve a high detection ratio (DR) but also decrease false alarm ratio (FAR), as well as time cost.

引用

页码：11217 / 11222

页数：6

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