Towards completely rotated Simplified Gabor Wavelets for fast facial feature point detection

Facial Feature point detection, and object detection in general, is not only a problem of accuracy but also a problem of computation time. Integral images provide fast computation time. Several classes of features working on these integral images have been introduced. So far in most cases only integral images of 0° and 45° have been used. We will present our first results of exploring the performance of additional 26.5° and 63.5° rotated integral images, which have been introduced several years ago but widely been ignored so far. As features we will use the so called Simplified Gabor Wavelets. The extension of the available feature set for pattern recognition tasks should reduce the number of used features and can save computation time in the later search process.