Review on multiview face detection and recognition

In this paper we have worked on multi view face detection and recognition problem, with two different approaches. They are human head pose estimation by subspace learning and recognizing side view face images by automatic landmark detection. In our approach experiments are conducted using Local Derivative Pattern (LDA) and Principal Component Analysis (PCA) algorithm on CMU Multi Pose Illumination and Expression Database (PIE) database. It is found that Subspace learning method performs better than automatic landmark detection approach.