Computer vision and deep learning can play an important role in mobile
devices the goal of face detection and recognition in mobile phones is not to
reproduce the same results as those obtained in computers. The main problem
facing the development of computer vision applications for mobile phones
concerns the limited resources such as CPU ,memory, storage and phone cameras
quality in order to make the face models calculations. The goal is to develop light
and smart algorithm by taking in consideration the mobile phone environment
limitation.
In this paper, a fast, reliable automatic human face and facial feature detection is
one of the initial and most important steps of face analysis and face recognition
systems for the purpose of localizing and extracting the face region from the
background. This paper presents a Crossed Face Detection Method that instantly
detects low resolution faces in still images or video frames. Experimental results
evaluated various face detection methods, providing complete solution for image
based face detection with higher accuracy, showing that the present method
efficiently decreased false positive rate and subsequently increased accuracy of
face detection system in still images or video frames especially in complex
backgrounds.