HUMAN FACE DETECTION USING MOBILE PHONES | ||||
| Journal of the ACS Advances in Computer Science | ||||
| Article 7, Volume 9, Issue 1, 2018, Page 109-133 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asc.2018.158385 | ||||
 View on SCiNiTO | ||||
| Abstract | ||||
| 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. | ||||
| Keywords | ||||
| Image processing; Algorithms; Mobile application; Face detection; Videos frames; Viola- Jones; Skin detection; Skin color classification | ||||
|
Statistics Article View: 104 |
||||
