Abstract
Automatic age estimation of facial images is a challenging problem in computer vision and image analysis as the process of aging is affected by different issues like gender, ethnicity, environment etc. Also to estimate near accurate age from facial images requires a large amount of data and tedious training period. In this paper, we have proposed an age estimator based on the Convolutional Neural Network (CNN) that can predict age from facial images almost accurately. Our approach requires less training data than the related works yet keeping a low Mean Absolute Error (MAE). We built a model on top of the 50 layer Residual Network named ResNet 50 that implements age estimation as a regression problem. Our experimental results are compared with other age estimation techniques. The comparison exhibits that the performance of our age estimation system is close to other related works even after training with a relatively smaller dataset.
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