  Face recognition in real-time scenarios is mainly affected by illumination,
expression and pose variations and also by occlusion. This paper presents the
framework for pose adaptive component-based face recognition system. The
framework proposed deals with all the above mentioned issues. The steps
involved in the presented framework are (i) facial landmark localisation, (ii)
facial component extraction, (iii) pre-processing of facial image (iv) facial
pose estimation (v) feature extraction using Local Binary Pattern Histograms of
each component followed by (vi) fusion of pose adaptive classification of
components. By employing pose adaptive classification, the recognition process
is carried out on some part of database, based on estimated pose, instead of
applying the recognition process on the whole database. Pre-processing
techniques employed to overcome the problems due to illumination variation are
also discussed in this paper. Component-based techniques provide better
recognition rates when face images are occluded compared to the holistic
methods. Our method is simple, feasible and provides better results when
compared to other holistic methods.
