1. A method for detecting an object using an AdaBoost based classifier, such as a face, in a digital image, the method comprising the following acts: selecting a sub-window of a digital image from a set of training sub-windows that are labeled as face or non-face sub-windows; extracting multiple sets of two symmetric scalar features from the sub-window; minimizing the joint error of the two symmetric features for each set of two symmetric scalar features; selecting one of the features from the set of two symmetric scalar features for each set of two symmetric scalar features; and linearly combining multiple weak classifiers, each of which corresponds to one of the selected features, into a stronger classifier.