• Nataliia Kuzmenko National Aviation University
  • Volodymyr Kharchenko National Aviation University
  • Ivan Ostroumov National Aviation University



UAS, artificial intelligence, Aggregate Channel Features, object detection, video-stream


Purpose: The paper is aimed to point out an artificial intelligence as a key priority for research and development issues. Consideration of existing methods of object detection is one of the important tasks of the paper. The represented research results are aimed to investigate a problem of moving object detection by visual sensor data for Unmanned Aerial System application. Methods: Represented approach is grounded on probabilistic and statistical methods of data processing, in particular on Aggregate Channel Features approach usage for object detection. Results: An Aggregate Channel Features approach for object detection by video-stream at different scenarios has been practically investigated. Results of experimental investigation of ACF usage for moving vehicles detection, such as cars and trams, indicate good performance characteristics. Also, a dependence between training time of detector and amount of object positive instances has been investigated for particular case. Discussion: Multiple advantages of Aggregate Channel Features object detector such as universality, simplicity of realization and good compromise between computation time and detection accuracy allow to use it in the tasks of people, vehicles, artificial and natural objects detection in UAS application. Represented results can be implemented in Unmanned Aerial Systems for searching and tracking of movable objects.

Author Biographies

Nataliia Kuzmenko, National Aviation University

Candidate of Engineering. Senior researcher.

National Aviation University.

Education: National Aviation University, Kyiv, Ukraine (2013).

Research area: navigation and control of dynamic systems, artificial intelligence.

Volodymyr Kharchenko, National Aviation University

Doctor of Engineering. Professor.

Vice-Rector on Scientific Work, National Aviation University, Kyiv, Ukraine.

Editor-in-Chief of the scientific journal Proceedings of the National Aviation University.

Winner of the State Prize of Ukraine in Science and Technology, Honored Worker of Science and

Technology of Ukraine.

Education: Kyiv Institute of Civil Aviation Engineers, Kyiv, Ukraine.

Research area: management of complex socio-technical systems, air navigation systems and automatic

decision-making systems aimed at avoidance conflict situations, space information technology design, air

navigation services in Ukraine provided by CNS/ATM systems.

Ivan Ostroumov, National Aviation University

Candidate of Engineering.

Associate Professor. National Aviation University.

Education: National Aviation University, Kyiv, Ukraine (2005).

Research area: Navigation, Alternative Position, Navigation and Timing.


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How to Cite

Kuzmenko, N., Kharchenko, V., & Ostroumov, I. (2019). AN INVESTIGATION OF AGGREGATE CHANNEL FEATURES OBJECT DETECTOR FOR UAS APPLICATION. Proceedings of National Aviation University, 78(1), 14–21.




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