Detection and tracking people in real-time with YOLO object detector

Aziza Srazhdinova, A. Ahmetova, S. Anvarov

2020

Full text Open access: Gold Metadata (CSL-JSON)

DOI 10.31643/2020.010

Data confidence 70 medium

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Abstract

In this article, we wrote not a large program to solve tasks for detection and tracking objects in realtime. The program was written in Python programming language. For object detection, a convolutional neural network was used with YOLOV3 architecture. A preliminary analysis was carried out of several variations of YOLO with CNN models. In the article, we justify why we want to use YOLO, and what it is and how to use and process the model output. We will also present the code in the form of a flowchart and as a result of the program's performance, we will show a picture of the program's operation in real-time, which was launched at one of the live lectures at the University.