YOLOv3-Based Human Activity Recognition as Viewed from a Moving High-Altitude Aerial Camera

Wazha Mmereki, Rodrigo S. Jamisola, Dimane Mpoeleng, Tinao Petso

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a method to classify human activities as normal or suspicious using YOLOv3 to automatically process video footages taken from a high altitude moving aerial camera, such as the one attached to a drone. We consider four human activities namely, jogging, walking, fighting, and chasing. Objects generally appear much smaller, with less visible features, when viewed from high altitudes. The reduced visible features make automatic human activity detection from ground surveillance cameras not applicable to the high altitude case. Through transfer learning, we modified existing pre-trained YOLOv3 convolutional neural networks (CNN's) and retrained with our own high aerial human action dataset. By so doing, we were able to customize YOLOv3 to detect, localize, and recognize aerial human activities in real-time as normal or suspicious. The proposed approach achieves a promising average precision accuracy of 82.30%, and average F1 score of 88.10% on classifying high aerial human activities. We demonstrated that YOLOv3 is a powerful approach and relatively fast for the recognition and localization of human subjects as seen from above.

Original languageEnglish
Title of host publication2021 International Conference on Automation, Robotics and Applications, ICARA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages241-246
Number of pages6
ISBN (Electronic)9780738142906
DOIs
Publication statusPublished - Feb 4 2021
Event2021 International Conference on Automation, Robotics and Applications, ICARA 2021 - Virtual, Prague, Czech Republic
Duration: Feb 4 2021Feb 6 2021

Publication series

Name2021 International Conference on Automation, Robotics and Applications, ICARA 2021

Conference

Conference2021 International Conference on Automation, Robotics and Applications, ICARA 2021
CountryCzech Republic
CityVirtual, Prague
Period2/4/212/6/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Optimization

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