{"title":"基于头部单视点的遮挡人脸检测新方法","authors":"T. Charoenpong, C. Nuthong, U. Watchareeruetai","doi":"10.1109/ECTICON.2014.6839761","DOIUrl":null,"url":null,"abstract":"Due to a problem of current research concerning with occlude face detection occurring when detecting occluded face captured from any viewpoint of head between -90 degrees to +90 degrees, we propose a new method to detect occluded face from a viewpoint of face by skin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, huskin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, human head with and without obstacle captured from any viewpoint of headman head with and without obstacle captured from any viewpoint of head between -90 degrees to +90 degrees around the head is used. Based on a criterion of skin ratio from two sides of head, accuracy rate of non-occluded face and occluded face detection is 86.29%, and 91.02%, respectively. Advantage of this method is that this method can detect occluded face such as helmet or mask from any viewpoint of head.","PeriodicalId":347166,"journal":{"name":"2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A new method for occluded face detection from single viewpoint of head\",\"authors\":\"T. Charoenpong, C. Nuthong, U. Watchareeruetai\",\"doi\":\"10.1109/ECTICON.2014.6839761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to a problem of current research concerning with occlude face detection occurring when detecting occluded face captured from any viewpoint of head between -90 degrees to +90 degrees, we propose a new method to detect occluded face from a viewpoint of face by skin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, huskin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, human head with and without obstacle captured from any viewpoint of headman head with and without obstacle captured from any viewpoint of head between -90 degrees to +90 degrees around the head is used. Based on a criterion of skin ratio from two sides of head, accuracy rate of non-occluded face and occluded face detection is 86.29%, and 91.02%, respectively. Advantage of this method is that this method can detect occluded face such as helmet or mask from any viewpoint of head.\",\"PeriodicalId\":347166,\"journal\":{\"name\":\"2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECTICON.2014.6839761\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECTICON.2014.6839761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for occluded face detection from single viewpoint of head
Due to a problem of current research concerning with occlude face detection occurring when detecting occluded face captured from any viewpoint of head between -90 degrees to +90 degrees, we propose a new method to detect occluded face from a viewpoint of face by skin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, huskin color ratio of two parts of head region. Head data is captured from any viewpoint between -90 degrees to +90 degrees of viewpoint of head. This method consists of four steps which are primary head regions extraction, head area identification, skin area segmentation, and classification. For first step, foreground is extracted by Mahalanobis distance and background subtraction. In second step, head area is extracted based on primary head region. In third step, skin area is segmented by using multi-skin color database. Head region is divided into two parts based on center of head. For fourth step, a criterion of skin ratio of two parts of head is used for classification. In this paper, occluded face is detected by a criterion of skin ratio from each side of head. To evaluate performance of the method, human head with and without obstacle captured from any viewpoint of headman head with and without obstacle captured from any viewpoint of head between -90 degrees to +90 degrees around the head is used. Based on a criterion of skin ratio from two sides of head, accuracy rate of non-occluded face and occluded face detection is 86.29%, and 91.02%, respectively. Advantage of this method is that this method can detect occluded face such as helmet or mask from any viewpoint of head.