Gabor Wavelet Based Pose Estimation for Face Recognition

One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In this work, we use a variation of Gabor wavelet transform for the representation of human face images to efficiently solve the pose estimation problem. Parameters of the Gabor wavelets, namely frequency and orientation, are adjusted to gain better performance. Principal Component Analysis is performed to reduce the dimensionality without a significant loss in the performance. Our results show that Gabor wavelet based filtering of images improves the performance of the pose estimation module.