Three-dimensional (3-D) face reconstruction is an important task in the field of computer vision. Although 3-D face reconstruction has been developing rapidly in recent years, large pose face reconstruction is still a challenge. That is because much of the information about a face in a large pose will be unknowable. In order to address this issue, we propose a 3-D face reconstruction algorithm (PIFR) based on 3-D morphable model. A model alignment formulation is developed in which the original image and a normalized frontal image are combined to define a weighted loss in a landmark fitting process, with the intuition that the original image provides more expression and pose information, whereas the normalized image provides more identity information. Our method solves the problem of face reconstruction of a single image of a traditional method in a large pose, works on arbitrary pose and expressions, and greatly improves the accuracy of reconstruction. Experiments on the challenging AFW, LFPW, and AFLW database show that our algorithm significantly improves the accuracy of 3-D face reconstruction even under extreme poses (±90 yaw angles).
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