Recognizing Faces Across Age Progressions and Under Occlusion
Steven Lawrence Fernandes, Josemin G. Bala · Recent Advances in Computer Science and Communications · 2017
Background: Recognizing human faces across image processing is a difficult task mainly when it comes to age variation and occluded images. Aging causes a lot of variation in the human face and occlusion makes it difficult for us to recognize image of a person. Human faces undergo changes due to aging. These changes are affected by different factors and are subject to different age groups. In the early ages, like the childhood the facial shape is of importance and later on during the adulthood texture variations like wrinkles and pigmentation is seen. Age variation brings a major problem to the systems which recognize faces. Further it found that the task of identification is being complicated due to occlusions. Recognizing faces under occlusion mainly consists of registration and classification and there is very less work done in both of these areas. Keywords: Face recognition, sparse representation, principal component analysis, nearest neighbor classifier.