FACE DETECTION AND RESTORATION UNDER OCCLUSIONS : A LITERATURE REVIEW

Abstract

One of the main challenges of the face recognition is occlusions. Occlusion in an image refers to hindrance in the view of an object. Face recognition which work in the presence of occlusions are core for the current needs in the field of identification of suspects, as criminals try to take advantage of the weaknesses among the implemented security systems by camouflaging themselves and occluding their face with eyeglasses, hair, hands, or covering their face with scarves and hats. Human face recognition under occlusion is broadly classified into 8 categories Karhunen-Loeve Expansion Method, Model Based Method, Correlation Based Method, Template Based Method, Feature Based Method, Geometric Based Method, Singular Value Decomposition Based Method and Neural Network Based Algorithm. The paper details the experiments and databases used to handle the problem of occlusion and the results obtained by different authors. Lastly, a comparison of various techniques is presented and some conclusions are drawn referring to the best outcomes.