Abstract
Viola and Jones introduce a fast face detection system which uses a cascaded structure that can achieve high detection rate and low false positive rate. Their system uses integral images to compute values from features. This thesis introduces two new types of integral images which are called triangle integral images and two corresponding features which are named triangle features. And this thesis proposes a method to lower training error by modifying Discrete AdaBoost. As results, to use triangle features can decrease the numbers of features; this research achieves lower false positive rate and fewer features are used.