title: Comparative study of human age estimation with or without preclassification of gender and facial expression.
abstract: Age estimation has many useful applications, such as age-based face classification, finding lost children, surveillance monitoring, and face recognition invariant to age progression. Among many factors affecting age estimation accuracy, gender and facial expression can have negative effects. In our research, the effects of gender and facial expression on age estimation using support vector regression (SVR) method are investigated. Our research is novel in the following four ways. First, the accuracies of age estimation using a single-level local binary pattern (LBP) and a multilevel LBP (MLBP) are compared, and MLBP shows better performance as an extractor of texture features globally. Second, we compare the accuracies of age estimation using global features extracted by MLBP, local features extracted by Gabor filtering, and the combination of the two methods. Results show that the third approach is the most accurate. Third, the accuracies of age estimation with and without preclassification of facial expression are compared and analyzed. Fourth, those with and without preclassification of gender are compared and analyzed. The experimental results show the effectiveness of gender preclassification in age estimation.
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, Seoul 100-715, Republic of Korea.
authors.forename: Dat Tien
authors.identifier: 0000-0002-6029-6849
authors.initials: DT
authors.lastname: Nguyen
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, Seoul 100-715, Republic of Korea.
authors.forename: So Ra
authors.initials: SR
authors.lastname: Cho
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, Seoul 100-715, Republic of Korea.
authors.forename: Kwang Yong
authors.initials: KY
authors.lastname: Shin
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, Seoul 100-715, Republic of Korea.
authors.forename: Jae Won
authors.initials: JW
authors.lastname: Bang
authors.affiliation: Division of Electronics and Electrical Engineering, Dongguk University, Seoul 100-715, Republic of Korea.
authors.forename: Kang Ryoung
authors.initials: KR
authors.lastname: Park
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging; D005149:Facial Expression; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000145:classification* / Q000379:methods / Q000592:standards*; D010775:Photic Stimulation / Q000379:methods; D012727:Sex Characteristics; D055815:Young Adult