{"title":"Facial feature detection: A facial symmetry approach","authors":"Gulbadan Sikander, S. Anwar, Y. Djawad","doi":"10.1109/ISCBI.2017.8053538","DOIUrl":null,"url":null,"abstract":"Nowadays face detection plays an important role in recognition, emotion recognition, computer-human interaction, etc. This paper presents a novel method for the detection of facial features in images. The main objective is to develop a fully automatic facial feature detection system. The method proposed in this paper uses a combination of methods to detect facial features. It first uses the Viola-Jones methods to identify possible regions of interest subsequently use calculations based on the symmetric property of the human face to detect the true facial features. A comparison between the Viola-Jones algorithm and the proposed algorithm has been performed and it shows that our method in combination with Viola-Jones increases the accuracy of detection considerably.","PeriodicalId":128441,"journal":{"name":"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Symposium on Computational and Business Intelligence (ISCBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCBI.2017.8053538","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Nowadays face detection plays an important role in recognition, emotion recognition, computer-human interaction, etc. This paper presents a novel method for the detection of facial features in images. The main objective is to develop a fully automatic facial feature detection system. The method proposed in this paper uses a combination of methods to detect facial features. It first uses the Viola-Jones methods to identify possible regions of interest subsequently use calculations based on the symmetric property of the human face to detect the true facial features. A comparison between the Viola-Jones algorithm and the proposed algorithm has been performed and it shows that our method in combination with Viola-Jones increases the accuracy of detection considerably.