Rapid object detection using a boosted cascade of simple features

"Rapid object detection using a boosted cascade of simple features," Paul Viola and Michael Jones, CVPR, 2001

The paper proposes a rapid object detection method and constructs a frontal face detection system to prove the idea. First, they brings the “integral image” calculation which lets feature evaluation faster. That is, do first pass to sum the region of pixels above and to the left of each location, and it is possible to get the sum of each rectangle in the image by using the values of four corners. Second, use Adaboost method to select important features as classifiers. Third, construct a cascade structure combining complex classifiers to increase the detection speed. In other words, simpler classifiers are used to reject most illegal instances, and then more complex classifiers are called to reduce false positive rates

In conclusion, the paper presents a really useful integral image method that speed up the following corresponding calculation, and the face system they constructs is the basis of face detection and cause more applications and improved techniques.