{"title":"Face Feature Extraction Using Elliptical Model Based Background Deletion and Generalized FEM","authors":"Yun-Su Chung, Sung-Uk Jung, Younglae Bae, Kiyoung Moon","doi":"10.1109/SITIS.2007.98","DOIUrl":null,"url":null,"abstract":"This paper addresses a new face feature extraction method using elliptical model based background deletion and the generalized facial energy map (FEM). First of all, the method utilizes the elliptical model of a face to get a good normalized face image. This elliptical model based approach, thus, can easily delete the background region of high complexity. Next, the method generates a generalized FEM from the transformed data set of normalized face images. Finally, the coefficients of DCT, potentially containing important meanings, are extracted with the above generalized FEM, and are analyzed by using LDA. Experimental results show that the method effectively extracts feature vectors with reasonable time complexity, and has good recognition performance.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2007.98","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper addresses a new face feature extraction method using elliptical model based background deletion and the generalized facial energy map (FEM). First of all, the method utilizes the elliptical model of a face to get a good normalized face image. This elliptical model based approach, thus, can easily delete the background region of high complexity. Next, the method generates a generalized FEM from the transformed data set of normalized face images. Finally, the coefficients of DCT, potentially containing important meanings, are extracted with the above generalized FEM, and are analyzed by using LDA. Experimental results show that the method effectively extracts feature vectors with reasonable time complexity, and has good recognition performance.