Abstract—This paper investigates the use of SVM-SMO algorithms in estimating the age of a person through the evaluation of its facial features on both front and side-view face orientation. Stephen-Harris algorithm, SURF, and Minimum Eigenvalue Feature Detection algorithms were also used for feature extraction. During experiments, training sets composed on 44 front view images and 44 side view images were used to train the network. Testing was performed to 140 front view images and 44 side view images. Result of the experiment shows age recognition of 53.85% for front view images and 14.3% for side view images.
Index Terms—age determination, image processing, neural networks
Cite: Julianson Berueco, Kim Lopena, Arby Moay, Mehdi Salemiseresht, and Chuchi Montenegro, "Age Estimation Using Support Vector Machine–Sequential Minimal Optimization," Journal of Image and Graphics Vol. 2, No. 2, pp.145-150, December 2014. doi: 10.12720/joig.2.2.145-150
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