{"title":"使用OpenCV进行低光环境下的人脸检测","authors":"Christopher Le, Tauheed Khan Mohd","doi":"10.1109/aiiot54504.2022.9817372","DOIUrl":null,"url":null,"abstract":"Detecting faces in low-light environments is an important new technology and have been under development for years. In surveillance, some security cameras with thermal technology can recognize humans based on the heat that the object radiates. However, with only thermal techniques, it is still challenging to recognize specific people. Recognizing human with heat vision makes it hard to tell the identity of the person with existing Computer Vision techniques such as CNN. In this research, we present a system to recognize human faces in a low-light environment by enhancing low-light images and applying facial detection to them. Another technique of image super-resolution will also be applied to enhance the quality of the images for better detection.","PeriodicalId":409264,"journal":{"name":"2022 IEEE World AI IoT Congress (AIIoT)","volume":"48 22","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Facial Detection in Low Light Environments Using OpenCV\",\"authors\":\"Christopher Le, Tauheed Khan Mohd\",\"doi\":\"10.1109/aiiot54504.2022.9817372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detecting faces in low-light environments is an important new technology and have been under development for years. In surveillance, some security cameras with thermal technology can recognize humans based on the heat that the object radiates. However, with only thermal techniques, it is still challenging to recognize specific people. Recognizing human with heat vision makes it hard to tell the identity of the person with existing Computer Vision techniques such as CNN. In this research, we present a system to recognize human faces in a low-light environment by enhancing low-light images and applying facial detection to them. Another technique of image super-resolution will also be applied to enhance the quality of the images for better detection.\",\"PeriodicalId\":409264,\"journal\":{\"name\":\"2022 IEEE World AI IoT Congress (AIIoT)\",\"volume\":\"48 22\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE World AI IoT Congress (AIIoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/aiiot54504.2022.9817372\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE World AI IoT Congress (AIIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aiiot54504.2022.9817372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Facial Detection in Low Light Environments Using OpenCV
Detecting faces in low-light environments is an important new technology and have been under development for years. In surveillance, some security cameras with thermal technology can recognize humans based on the heat that the object radiates. However, with only thermal techniques, it is still challenging to recognize specific people. Recognizing human with heat vision makes it hard to tell the identity of the person with existing Computer Vision techniques such as CNN. In this research, we present a system to recognize human faces in a low-light environment by enhancing low-light images and applying facial detection to them. Another technique of image super-resolution will also be applied to enhance the quality of the images for better detection.