Face Detection Using Machine Learning Algorithms

Abstract

In recent years, face recognition has attracted much attention and its research has rapidly expanded by not only engineers but also neuroscientists since it has many potential applications in computer vision communication and automatic access control system. Especially, face detection is an important part of face recognition as the first step of automatic face recognition. However, face detection is not straightforward because it has lots of variations of image appearance, such as pose variation (front, non-front), occlusion, image orientation, illuminating condition and facial expression. Many novel methods have been proposed to resolve each variation listed above. Nevertheless, implementing the methods altogether is still a great challenge. Fortunately, the images used in this project have some degree of uniformity thus the detection algorithm can be simpler: first, all the faces are vertical and have a frontal view; second, they are under almost the same illuminate condition. There is some work done on this specific problem, but we propose an approach to detect face in realtime by machine learning which will fulfill the requirements. We have applied some machine learning algorithms to our collected dataset’s features and got promising results. And our model will help by detecting the face in real-time.