Pose-invariant face recognition based on a flexible camera calibration

Abstract

In this paper, we present a flexible camera calibration for pose normalization to accomplish a pose-invariant face recognition. The accuracy of calibration can be easily influenced by errors of landmark detection or various shapes of different faces and expressions. By jointly using RANSAC and facial unique characters, we explore a flexible calibration method to achieve a more accurate camera calibration and pose normalization for face images. Our proposed method is able to eliminate noisy facial landmarks and retain the ones which best match the undeformable 3D face model. The experimental results show that our method improves the accuracy of pose-invariant face recognition, especially for the faces with unsatisfied landmark detection, variant shapes, and exaggerated expressions.