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Conference Paper
Human Age Estimation Using Multi-Class SVM
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- Authors
- Kyekyung Kim, Sangseung Kang, Sooyoung Chi, Jaehong Kim
- Issue Date
- 2015-10
- Citation
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2015, pp.370-372
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Age estimation from face images has attracted attention because it is expected to have many application fields and growing interest. Human age estimation is very difficult tasks because a person has a different in appearance, which varies along with environment even same age. And also, pose, lighting condition or expression has an effect to estimate human age. Age estimation has challenged due to aforementioned problem even it has various potential application fields. In this paper, age estimation using Gabor feature and support vector machine as a classifier has proposed. Age-specific face images has saved in database, which has captured in real world environment. Age estimation result has applied to interact with sports simulator, which provides specialized information to each person, who wants to get individualized exercise model on sports simulator. We have evaluated age estimation performance on ETRI database, which has constructed during several months in real world environment.
- KSP Keywords
- Application fields, Face image, Gabor feature, Human age estimation, Lighting condition, Multi-class SVM, Potential applications, Real-world, Sports simulator, Support VectorMachine(SVM), estimation performance