Imam Husni Al Amin, Falah Hikamudin Arby, Edy Winarno, B. Hartono, W. Hadikurniawati
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引用次数: 0
摘要
2019年底以来,新冠肺炎疫情在全球持续蔓延。所有人还执行不感染这种疾病的卫生协议。必须实施的一项卫生协议是将人与人之间的互动限制在1-2米的长度,或通常与社交距离保持一致。确保人们不违反社交距离的社交距离检测系统可能是解决这一问题的一个办法。该系统的检测速度高达每秒140帧(FPS),比以前的YOLO (You Only Look Once)方法低90%,是最新版本的YOLO-v5方法,它可以检测出违反社交距离的人,然后发出声音警告,让他们保持距离,以免传播新冠病毒。检测系统中人的检出率达到93.5%,社会距离检测准确率达到95%。根据已经完成的研究,可以说该系统可以很好地检测社交距离,但检测将开始检测相机与物体之间的距离超过10米。
Real-time Social Distance Detection using YOLO-v5 with Bird-eye View Perspective to Suppress the Spread of COVID-19
The COVID-19 virus outbreak has continued to spread since the end of 2019 worldwide. All people also implement health protocols not to contract this disease. One of the health protocols that must be implemented is to limit interactions between humans to a length of 1–2 meters or what is usually done with social distancing. Social distance detection system to ensure that people do not violate social distancing could be a solution to this problem. Using the YOLO-v5 method, which is the latest version of the YOLO (You Only Look Once) method with a detection speed of up to 140 Frames Per Second (FPS) and 90 percent smaller than the previous version, this system detects people who violate social distancing and then gives a voice warning to keep their distance to avoid spreading the COVID-19 virus. The human detection rate in the detection system reaches 93,5%, and the accuracy for social distance detection reaches 95%. Based on the research that has been done, it can be said that this system can work well for detecting social distance, but the detection will start detecting the distance between the camera and the object exceeding 10 meters.