Unified 3D Face and Ear Recognition using Wavelets on Geometry Images

As the accuracy of biometrics improves, it is getting increasingly hard to push the limits using a single modality. In this paper, a unified approach that fuses three-dimensional facial and ear data is presented. An annotated deformable model is fitted to the data and a geometry image is extracted. Wavelet coefficients are computed from the geometry image and used as a biometric signature. The method is evaluated using the largest publicly available database and achieves 99.7% rank-one recognition rate. The state-of-the-art accuracy of the multimodal fusion is attributed to the low correlation between the individual differentiability of the two modalities.