FRONT SEAT CHILD OCCUPANCY DETECTION USING ROAD SURVEILLANCE CAMERA IMAGES

被引:0
|
作者
Balci, Burak [1 ]
Alkan, Bensu [1 ]
Elihos, Alperen [1 ]
Artan, Yusuf [1 ]
机构
[1] HAVELSAN Inc, Ankara, Turkey
关键词
Traffic Enforcement; Convolutional Neural Network; Face Detection; Image Classification;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Camera based traffic enforcement solutions has been ubiquitously employed in many roadways around the world. Toll violation detection, red light violation detection, speed violation detection are typically the most common usages of camera systems towards traffic enforcement. However, there are other enforcement areas that need attention such as front seat child occupancy violation, which is a major safety concern in many countries. In this study, we propose a novel automated technique towards child occupancy detection in front seat of vehicles using deep learning algorithms. Using a camera system placed on an overhead gantry, installed on a high way in Turkey, real world images are captured during day and night time. We performed experiments using 1000 real world images and achieved an overall accuracy of 92 %.
引用
收藏
页码:1927 / 1931
页数:5
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