An approach to face shape classification for hairstyle recommendation

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dc.contributor.authorSunhem, Wisuwat
dc.contributor.authorPasupa, Kitsuchart
dc.date.accessioned2026-08-06T10:13:44Z
dc.date.available2026-08-06T10:13:44Z
dc.date.issued2016-04-07
dc.description.abstractIt is important to choose a good hairstyle for women because it can enhance their beauty, personality, and confidence. One of the most important factors to consider for choosing the right hairstyle is the individuals face shape. An effective face shape classification can be used for constructing a hairstyle recommendation system. This paper presents a classification approach that divides face shapes into 5 different shapes: round, oval, oblong, square, and heart. This approach, which is based on an Active Appearance Model (AAM) and a face segmentation technique, produces a set of features that can be evaluated by several popular machine learning methods, namely, Linear Discriminant Analysis (LDA), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). Our results show that the Support Vector Machine with Radial Basis function kernel was the best algorithm that predicted accurately up to 72%.
dc.identifier.citationProceedings of the 8th International Conference on Advanced Computational Intelligence Icaci 2016, 390-394, 2016
dc.identifier.doi10.1109/ICACI.2016.7449857
dc.identifier.other2-s2.0-84966565085
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/6854
dc.sourceProceedings of the 8th International Conference on Advanced Computational Intelligence Icaci 2016
dc.subjectface shape classification
dc.subjecthairstyle recommendation
dc.subjectmachine learning
dc.titleAn approach to face shape classification for hairstyle recommendation
dc.typeConference Paper

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