Asymmetric boosting, while acknowledged to be
important to state-of-the-art face detection, is
typically based on the trial-and-error practice,
rather than on principled methods. This work solves a
number of issues related to asymmetric boosting and
the use of asymmetric boosting in face detection. It
shows how a proper understanding and use of
asymmetric boosting leads to significant improvements
in the
learning time, the learning capacity, the detection
speed and the detection accuracy of a face detector.

There are four main contributions in this book: 1) a
new method to learn online an...