{"title":"基于均匀局部梯度模式和AdaBoost算法的鲁棒人脸检测","authors":"Jun-Gyu Park, D. Kang","doi":"10.1109/MAS.2015.11","DOIUrl":null,"url":null,"abstract":"Facial feature detection has been applied in many devices, such as cameras, smartphones, and CCTV. Most importantly, face detection should detect a face without a significant effect from external factors, such as changes in lighting, background, and so on. In this study, to be robust against external factors and to select the pattern, we propose a specified accuracy that is a better algorithm. The proposed algorithm is used to extract facial features from the LGP algorithm robust to external factors when detecting facial features. The facial features are the eyes, nose, and mouth, thereby learning by specifying a pattern. Using the training set a face is detected.","PeriodicalId":446137,"journal":{"name":"2015 4th International Conference on Modeling and Simulation (MAS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Robust Face Detection Using Uniform Local Gradient Pattern (ULGP) and AdaBoost Algorithm\",\"authors\":\"Jun-Gyu Park, D. Kang\",\"doi\":\"10.1109/MAS.2015.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Facial feature detection has been applied in many devices, such as cameras, smartphones, and CCTV. Most importantly, face detection should detect a face without a significant effect from external factors, such as changes in lighting, background, and so on. In this study, to be robust against external factors and to select the pattern, we propose a specified accuracy that is a better algorithm. The proposed algorithm is used to extract facial features from the LGP algorithm robust to external factors when detecting facial features. The facial features are the eyes, nose, and mouth, thereby learning by specifying a pattern. Using the training set a face is detected.\",\"PeriodicalId\":446137,\"journal\":{\"name\":\"2015 4th International Conference on Modeling and Simulation (MAS)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 4th International Conference on Modeling and Simulation (MAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MAS.2015.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 4th International Conference on Modeling and Simulation (MAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAS.2015.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust Face Detection Using Uniform Local Gradient Pattern (ULGP) and AdaBoost Algorithm
Facial feature detection has been applied in many devices, such as cameras, smartphones, and CCTV. Most importantly, face detection should detect a face without a significant effect from external factors, such as changes in lighting, background, and so on. In this study, to be robust against external factors and to select the pattern, we propose a specified accuracy that is a better algorithm. The proposed algorithm is used to extract facial features from the LGP algorithm robust to external factors when detecting facial features. The facial features are the eyes, nose, and mouth, thereby learning by specifying a pattern. Using the training set a face is detected.