{"title":"一种基于边缘的人脸检测算法,对光照、焦点和尺度变化具有鲁棒性","authors":"Yasufumi Suzuki, T. Shibata","doi":"10.5281/ZENODO.38646","DOIUrl":null,"url":null,"abstract":"A face detection algorithm very robust against illumination, focus and scale variations in input images has been developed based on the edge-based image representation. The multiple-clue face detection algorithm developed in our previous work has been employed in conjunction with a new decision criterion called “density rule,” where only high density clusters of detected face candidates are retained as faces. As a result, the occurrence of false negatives has been greatly reduced. The robustness of the algorithm against circumstance variations has been demonstrated.","PeriodicalId":347658,"journal":{"name":"2004 12th European Signal Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"An edge-based face detection algorithm robust against illumination, focus, and scale variations\",\"authors\":\"Yasufumi Suzuki, T. Shibata\",\"doi\":\"10.5281/ZENODO.38646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A face detection algorithm very robust against illumination, focus and scale variations in input images has been developed based on the edge-based image representation. The multiple-clue face detection algorithm developed in our previous work has been employed in conjunction with a new decision criterion called “density rule,” where only high density clusters of detected face candidates are retained as faces. As a result, the occurrence of false negatives has been greatly reduced. The robustness of the algorithm against circumstance variations has been demonstrated.\",\"PeriodicalId\":347658,\"journal\":{\"name\":\"2004 12th European Signal Processing Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 12th European Signal Processing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.38646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 12th European Signal Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.38646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An edge-based face detection algorithm robust against illumination, focus, and scale variations
A face detection algorithm very robust against illumination, focus and scale variations in input images has been developed based on the edge-based image representation. The multiple-clue face detection algorithm developed in our previous work has been employed in conjunction with a new decision criterion called “density rule,” where only high density clusters of detected face candidates are retained as faces. As a result, the occurrence of false negatives has been greatly reduced. The robustness of the algorithm against circumstance variations has been demonstrated.