Stable Local feature based Age Invariant Face Recognition
Jyothi S. Nayak, M. Indiramma · 2013
Face recognition is identifying a person based on facial characteristics. Automated face recognition is identifying a given query face called probe from a target population known as gallery. The face recognition algorithms perform well when the interpersonal images have more discriminating features than intra personal images. The changes in the face bring down the similarity of the intrapersonal images. The variations in the face can be due to pose, expression, illumination changes and aging of a person. Face recognition accuracy is largely influenced by the age related changes in face. Aging effects on face are not uniform and depends on both intrinsic as well as external factors like geographic location, race, and food habits etc. The facial changes are exclusive for each person in spite of aging being an apparent phenomenon among all individuals. Hence there are many challenges lie in compensating age related variations.In this paper we concentrate on local features of the face which are relatively stable with respect to aging. We compute the local binary pattern of the various facial regions and recognize the query image based on the similarity of the local binary pattern histograms. The recognition rate is improved by giving weightage to the features which are stable across aging.