Constructing efficient cascade classifiers for object detection

The effectiveness of the cascaded object detector has been demonstrated repeatedly, and the basic steps to generate one are well known. But it is not obvious how to ensure the resulting detector will be efficient. This paper offers a solution by introducing a performance criterion that combines detection rate, false positive rate and speed, and a new cost function based on two simple, rational objectives. The result is a novel method for structuring the cascade which consistently produces efficient classifiers.