KERNEL ELM BASED AGE ESTIMATION

Furkan Gürpınar, Heysem Kaya, Sadaf Afshar, Hamdi Dibeklioğlu, Albert Ali Salah
786 259

Öz


This paper presents a framework for estimating the apparent age of a subject from their face image. To learn the age estimation model, we used a set of visual descriptors and their feature-level fusion to obtain a single feature vector for apparent age. For model learning, we used regression with Extreme Learning Machines (ELM) with Gaussian (RBF) kernels. We tested the proposed system with k-fold cross-validation on the dataset provided by ChaLearn Looking at People 2015 - Apparent Age Estimation challenge. By combining visual descriptors from multiple grids, we obtained a Mean Absolute Error (MAE) of 5.20.


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