Frequency guided bilateral symmetry Gabor Wavelet Network

We propose a bilateral symmetry Gabor Wavelet Network (BSGWN) for face modeling and online tracking. Bilateral symmetry wavelet pairs reduce the computational complexity of the BSGWN optimization and yield robust tracking performance in real world environments. We decompose face image into a set of frequency components. The face model of Gabor wavelets is built on the reconstructed image from corresponding frequency bands of wavelets used. The frequency guidance allows fast and accurate face tracking by removing potential clutters from other frequency bands. We verify the proposed algorithm on real video sequences including various challenging face conditions.