A Survey: Face Recognition Techniques under Partial Occlusion

Systems that rely on Face Recognition (FR) biometric have gained great importance ever since terrorist threats imposed weakness among the implemented security systems. Other biometrics i.e., fingerprints or iris recognition is not trustworthy in such situations whereas FR is considered as a fine compromise. This survey illustrates different FR practices that laid foundations on the issue of partial occlusion dilemma where faces are disguised to cheat the security system. Occlusion refers to facade of the face image which can be due to sunglasses, hair or wrapping of facial image by scarf or other accessories. Efforts on FR in controlled settings have been in the picture for past several years; however identification under uncontrolled conditions like illumination, expression and partial occlusion is quite a matter of concern. Based on literature a classification is made in this paper to solve the recognition of face in the presence of partial occlusion. These methods are named as part based methods that make use of Principal Component Analysis (PCA), Linear Discriminate Analysis (LDA), Non-negative Matrix Factorization (NMF), Local Non-negative Matrix Factorization (LNMF), Independent Component Analysis (ICA) and other variations. Feature based and fractal based methods consider features around eyes, nose or mouth region to be used in the recognition phase of algorithms. Furthermore the paper details the experiments and databases used by an assortment of authors to handle the problem of occlusion and the results obtained after performing diverse set of analysis. Lastly, a comparison of various techniques is shown in tabular format to give a precise overview of what different authors have already projected in this particular field.