Development of Partial Face Recognition Framework
Han Foon Neo, Chuan Chin Teo, Andrew Beng Jin Teoh · 2010
This paper presents a new framework of face recognition system that utilizes partial information available from front face where the users are willing and able to provide for access control. It is especially useful for people where part of their face is scarred and defect thus need to be covered. Hence, either top part/eye region (people is wearing veil or mask) or bottom part of face (people is wearing sunglasses) will be recognized respectively. The partial face data are tested with Principle Component Analysis (PCA), Non-negative matrix factorization (NMF), Local NMF (LNMF) and Spatially Confined NMF (SFNMF). The experiment results show that our proposed framework is able to achieve recognition rate of 95.17% with r = 80 by using SFNMF for bottom face region. On the other hand, eye region achieves 95.12% with r = 10 by using LNMF.