Frontal face classifier using AdaBoost with MCT features
Jongmin Yoon, Daijin Kim · 2010
In this paper, we describe how to classify frontal face from the results of face detection which include non-frontal faces. To do this, we use AdaBoost learning method with Modified Census Transform (MCT) to construct a two-class classifier. As a result of that, our frontal face classifier achieves high classification rate above 96% and fast performance about 10 frames/sec in mobile device.