中圖分類(lèi)號(hào)： TP391
文獻(xiàn)標(biāo)識(shí)碼： A
DOI：10.16157/j.issn.0258-7998.201100
中文引用格式： 祁星晨，卓旭升. 基于改進(jìn)MTCNN算法的低功耗邊緣人臉檢測(cè)跟蹤系統(tǒng)[J].電子技術(shù)應(yīng)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