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Age and Gender Estimation based on Multiple patterns and Multiple features

Title
Age and Gender Estimation based on Multiple patterns and Multiple features
Authors
Kim, HyundukLee, Sang HeonHwang, Byung HunKim, Yoon JibAhn, Young Sun
DGIST Authors
Kim, Hyunduk; Lee, Sang Heon
Issue Date
2018-02-01
Citation
ISIITA 2018
Type
Conference
Abstract
Human age and gender are valuable demographic characteristics. They are also important soft biometric traits useful for human identification or verification. In this paper, we propose an age and gender estimation framework based on multiple patterns and multiple features. The proposed approach consists of three process. First step is landmark based face alignment. Second step is feature extraction step. In this process, we define multiple patterns from face region. And then, we combine multiple features extracted from multiple patterns. Finally, we classify age and gender using a multi-layered Support Vector Machines (SVM) for efficient classification. Rather than performing gender estimation and age estimation independently, the use of the multi-layered SVM can improve the classification rate by constructing a classifier that estimate the age according to gender. Moreover, we collect a dataset of face images, called by DGIST_C, from the internet. Our dataset consists of about 20K Korean celebrities, labeled for age, gender.
URI
http://hdl.handle.net/20.500.11750/15112
Publisher
International Society for Information Technology and Application
Related Researcher
Files:
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Collection:
Division of Automotive Technology2. Conference Papers


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