Abstract
Face detection has been widely studied by researchers. However, detection and extraction of human face features is very important as it plays a vital role in variety of applications involving automated face processing. This article focuses on extraction of face parts such as eyes, nose, lips, musta che, and beard on Indian people, for which we have prepared our own face dataset containing variety in faces, from both urban and rural areas. This study focuses on how a detected face part becomes useful in detecting other face parts. We implement our approaches of detecting face parts and evaluate them on our dataset. We exploit YCbCr color model, Viola Jones technique, landmark detection, and level set evolution technique in our approaches of face part detection and extraction. We found that our approaches are effective on extracting face boundary, eyes, nose, and lips and provide comparable results.
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