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논문검색

Technology Convergence (TC)

A study on object distance measurement using OpenCV-based YOLOv5

원문정보

초록

영어

Currently, to prevent the spread of COVID-19 virus infection, gathering of more than 5 people in the same space is prohibited. The purpose of this paper is to measure the distance between objects using the Yolov5 model for processing real-time images with OpenCV in order to restrict the distance between several people in the same space. Also, Utilize Euclidean distance calculation method in DeepSORT and OpenCV to minimize occlusion. In this paper, to detect the distance between people, using the open-source COCO dataset is used for learning. The technique used here is using the YoloV5 model to measure the distance, utilizing DeepSORT and Euclidean techniques to minimize occlusion, and the method of expressing through visualization with OpenCV to measure the distance between objects is used. Because of this paper, the proposed distance measurement method showed good results for an image with perspective taken from a higher position than the object in order to calculate the distance between objects by calculating the y-axis of the image.

목차

Abstract
1. INTRODUCTION
2. RELATED RESEARCH
2.1 Yolo5 Model
2.2 DeepSORT
3. DESIGN OF SYSTEM
3.1 COCO dataset
3.2 YoloV5 Model
3.3 Distance measurement process between objects on an image
4. IMPLEMENT AND RESULT
4.1 Testing of Yolov5 Model
4.2 Result
5. CONCLUSION
REFERENCES

저자정보

  • Hyun-Tae Kim student., Computer Engineering, Honam University, Korea
  • Sang-Hyun Lee Associate Professor., Department of Computer Engineering, Honam University, Korea

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