中图分类号： TP391
文献标识码： A
DOI：10.16157/j.issn.0258-7998.201100
中文引用格式： 祁星晨，卓旭升. 基于改进MTCNN算法的低功耗边缘人脸检测跟踪系统[J].电子技术应用，2021，47(5)：40-44.
英文引用格式： Qi Xingchen，Zhuo Xusheng. Low-power edge AI face detection and tracking system based on improved MTCNN algorithm[J]. Application of Electronic Technique，2021，47(5)：40-44.

Low-power edge AI face detection and tracking system based on improved MTCNN algorithm

Abstract： The rapid development of edge devices and the application of deep learning are increasing, the trend of combining the two is becoming more and more obvious. The potential of AI applications for low-power edge devices has not yet been fully developed. A large number of devices hide a lot of computing power. The social and economic benefits brought by the release of its potential are very obvious. Therefore, taking the more common face detection in objective detection tasks as an example, the MTCNN face detection algorithm is improved and transplanted to a low-power embedded platform with extremely limited resources. Under certain environmental conditions, the face is finally successfully detected,and the face candidate boundingbox is drawn, it has face tracking function combined with the servo.

Key words : low-power edge devices；object detection；face detection and tracking；cascaded convolutional neural network