Fast Human Recognition System on Real-Time Camera

Authors

  • Yuliza Yuliza Universitas Mercu Buana Jakarkta
  • Rachmat Muwardi Universitas Mercu Buana Jakarkta
  • Mustain Rhozaly Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Lenni Lenni Department of Electrical Engineering, Universitas Muhammadiyah Tangerang, Tangerang, Indonesia
  • Mirna Yunita School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
  • Galatia Erica Yehezkiel School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

DOI:

https://doi.org/10.26555/jiteki.v9i4.27009

Keywords:

YOLO, Optimization, Image Processing, Computer Vision, Object Detection

Abstract

Technology development is very rapid, so all fields are required to develop technology to increase the effectiveness and efficiency of work. One of the focuses is related to image processing technology. We can get many benefits by implementing this system, so various fields have implemented image processing systems, such as security, health, and education. One of the current obstacles is in the area of safety, namely in the field of searching for people, which is still done manually. Often search teams find it challenging to find people because of the significant search area, low light conditions, and complex search fields. Therefore, we need a tool capable of detecting humans to assist in finding people. Therefore, to detect human objects, the authors try to research human object detection using a simple device for the human object detection system. The authors use the You only look once (YOLO) method with the YoloV4-Tiny type, where this algorithm has high detection speed and accuracy. Using the YOLOV4-Tiny simulation method for human object recognition, a detection rate of 100% is obtained with an FPS value of 5.

Downloads

Published

2023-09-30

Issue

Section

Articles