This book presents the most recent achievements in the field of a very fast developing Computer Science. It is a very fascinating science, which still encompasses a number of uncovered areas of study with urgent problems to be solved. Therefore, thousands of scientists are dealing with it elaborating on more and more practical and efficient methods. It is likely that their work will soon result in construction of a very effective, artificial computer-brain.
Effective and fast face feature extraction and reliable face feature representation is a key problem in many applications. The most important areas involved in implementing good solutions for that problem are: human-computer interaction, face biometrics, interpretation of face expression, face coding and face tracking. Even though there are many known methods of face detection in images, face feature extraction and representation, still the performance of real-time recognition systems, e.g. for biometrics human identification, is not satisfactory.
In general face feature extraction and representation can be appearance based, 2D geometry based or 3D model based. Since it is difficult to achieve reliable invariance to changing viewing conditions (rotation in depth, pose changes) while basing on 2D geometry  and 3D models techniques , currently most of the algorithms are appearance based and use PCA or its derivatives ICA and LDA  .
Another popular approach, which is based on Gabor Wavelets, is also appearance based, but local features are computed in the specified points as Gabor filtration coefficients (responses). Such approach relies on filtering the face image by the bank of Gabor filters. Then faces can be efficiently represented by the filter coefficients (so called Gabor Jets) calculated in the extracted fiducial (characteristic) points   . It is mainly because Gabor Wavelets are invariant to some degree to affine deformations and homogeneous illumination changes.