Real Time Face Detection System Using Adaboost and Haar-like Features

Face detection is widely used in interactive user interfaces and plays a very important role in the field of computer vision. In order to build a fully automated system that can analyze the information in face image, there is a need for robust and efficient face detection algorithms. One of the fastest and most successful approaches in this field is to use Haar-like features for facial appearance and learning these features by AdaBoost algorithm. The key advantage of a Haar-like feature over most other features is its calculation speed. Due to the use of integral images, a Haar-like feature of any size can be calculated in constant time, which greatly accelerates the detection speed, while AdaBoost algorithm is a good way to select a good set of weak learners to construct a strong classifier. In this paper, a real time face detection system using framework of Adaboost and Haar-like feature is developed. In the end, the experiments show high performance in both accuracy and speed of the developed system.