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摘要
It is know that face detection as a kind of artificial intelligence (AI) technology has become an indispensable tool in our daily life, which produce effects on every aspect of us. The demand for detection and recognition is higher accuracy and higher speed in different areas. So a new video frame-based face detection system is designed to help us making good safety precautions in recognition between normal face and abnormal face. Abnormal face means that face is partially occluded by some objects such as mask, sunglass and so on. Since these abnormal faces are easily recognized as normal faces in previous detection systems, they are often ignored. And it brings us some potential dangers, especially in the area of residential face detection access, bank business login and other security areas. This system provides a complete set of process for detecting faces from video and distinction them, which achieves a good real-time performance in accuracy and speed. We adopt libfacedetection to detect faces from each frame. In addition, we introduce a dlib library which is a deep learning tools to help aligning face and extract the characteristic value. And a GMM clustering algorithm is provided to train and test images for the system. This system can help us to make a distinction between normal face and abnormal face, which is of great significance to the security field in the future.
- 出版日期2018-8
- 单位合肥工业大学
