Haar-like features are very useful image features used in object detection. They were introduced in the first real-time face detector by Viola and Jones. Using integral images, Haar-like features of any size (scale) can be efficiently computed in constant time. The computation speed is the key advantage of a Haar-like feature over most other features. These features are just like the convolution kernels (rectangle filters) introduced in Chapter 3, Convolution and Frequency Domain Filtering. Each feature corresponds to a single value computed by subtracting a sum of pixels under a white rectangle from a sum of pixels under a black rectangle. The next diagram shows different types of Haar-like features, along with the important Haar-like features for face detection:
The first and the second important feature for face detection shown here seems to focus on the fact that the region of the eyes is often darker than the region of the nose and cheeks, and that the eyes are darker...
