Efficient face orientation discrimination

The paper presents efficient methods to address the problem of discriminating between live facial orientations. We present the most efficient methods for this task to date, which can accurately discriminate between five facial orientations with approximately 92% accuracy using fewer than 30 pixel comparisons and greater than 99% accuracy using 150 pixel comparisons. We achieve these rates by using a boosting method to select from a large set of extremely simple features. Comparisons to other methods are given.