A quantitative evaluation for 3D face reconstruction algorithms

In this work, we proposed to use quantitative method to evaluate the accuracy of 3D face reconstruction algorithms. The reconstructed 3D faces are first aligned to the ground truth by Iterative Closest Point (ICP) algorithm and then the shape difference between the two 3D faces is described by Signal to Noise Ratio (SNR). Finally, the error maps (EM) illustrated the reconstruction errors on corresponded vertices in different dimensions. Comparing with the subjective and indirect evaluation methods, the proposed method provides more precise and detailed evaluations for face shape reconstruction. Based on the SNR, different 3D face reconstruction algorithms can be compared directly and the EM also can suggest guidance for feature extraction.