Face Detection and Tracking Based on Neural Network

Jiao-yang Li, Chuan Yang, Fan Yang, Jie Huang, Wei Wei, Sujuan Zhang, Xun Zuo, Shilong Zhang
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Abstract

Face detection and tracking technology is used in transportation, security, military fields. In view of the traditional face detection and tracking technology is easy to be affected by light, which leads to low detection accuracy, this paper uses Retinaface and Camshift algorithm to face detection, and realizes real time face detection and tracking by P control steering gear in PID control. Through tests in different environments, the detection accuracy of the Retinaface algorithm and the Camshift algorithm is above 99%. The camera is rotated through P to ensure that the face can be captured by the camera, and the camera response time can reach 0.1s.
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基于神经网络的人脸检测与跟踪
人脸检测与跟踪技术应用于交通、安防、军事等领域。针对传统的人脸检测与跟踪技术容易受到光线的影响,导致检测精度不高的问题,本文采用Retinaface和Camshift算法进行人脸检测,并在PID控制中通过P控制舵机实现实时人脸检测与跟踪。通过在不同环境下的测试,retaface算法和Camshift算法的检测准确率均在99%以上。摄像头通过P旋转,保证摄像头能够捕捉到人脸,摄像头响应时间可以达到0.1s。
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