3D Facial Reconstruction from 2D Portrait Imagery

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Abstract:

3D facial images are reconstructed from 2D portraits using regression trees for facial landmark alignment and 3D morphable models. Two generic regression trees were adopted, one being based on the widely used 68-landmark structure, and the other based on a 74-landmark structure. The FaceWarehouse dataset was used to create a novel 74-landmark regression tree and during the system’s evaluation. The accuracy of the models generated was computed through the Root Mean Square, 75th Percentile and Arithmetic Mean comparison metrics. Two different datasets of 2D images were reconstructed. The evaluation results demonstrate that a higher level of accuracy and precision was attained from the models reconstructed using 68-landmark regression tree when compared to the 74 developed here. The accuracy produced by the 68-landmark regression tree applied to two sets was 85 % and 90 % as opposed to the 82 % and 83 % produced by the 74-landmark regression tree on the same model subsets; thus justifying its wide adoption.