南京航空航天大学学报（英文版）2021，Vol.38Issue(z1)：122-128,7.
红外热像和大数据用于检测发热人群和高危地区
Infrared Thermography and Big Data for Detection of People with Fever and Determination of High?Risk Areas in Epidemic Situations
TAMAYO FREIRE Alexis Shipson1
作者信息
- 1. 南京航空航天大学电子信息工程学院,南京 211106,中国
- 折叠
摘要
Abstract
Technological advances in computer science and their application in our daily life allow us to improve our understanding of problems and solve them effectively. A system design to detect people with fever and determine high-risk areas using infrared thermography and big data is presented. In order to detect people with fever,face detection algorithms of Viola-Jones and Kanade-Lucas are investigated,and comparison between them is presented using a training set of 406 thermal images and a test set of 2072 thermal images. Thermography analysis is performed on detected faces to obtain the temperature level on Celsius scale. With this information a sample database is created. To perform big data experimental analysis,Power Bi tool is used to determine the high-risk area. The experimental results show that Viola-Jones algorithm has a higher performance recognizing faces of thermal images than Kanade-Lucas,having a high detection rate,less false-positives rate and false-negatives rate.关键词
人脸检测/热成像/图像分析/大数据Key words
face detection/thermography/image analysis/big data分类
信息技术与安全科学引用本文复制引用
TAMAYO FREIRE Alexis Shipson..红外热像和大数据用于检测发热人群和高危地区[J].南京航空航天大学学报（英文版）,2021,38(z1):122-128,7.
