PROBABILISTIC APPROACH TO OBJECT DETECTION AND RECOGNITION FOR VIDEOSTREAM PROCESSING

Abstract

Purpose: The represented research results are aimed to improve theoretical basics of computer vision and artificial intelligence of dynamical system. Proposed approach of object detection and recognition is based on probabilistic fundamentals to ensure the required level of correct object recognition. Methods: Presented approach is grounded at probabilistic methods, statistical methods of probability density estimation and computer-based simulation at verification stage of development. Results: Proposed approach for object detection and recognition for video stream data processing has shown several advantages in comparison with existing methods due to its simple realization and small time of data processing. Presented results of experimental verification look possible for object detection and recognition in video stream. Discussion: The approach can be implemented in dynamical system within changeable environment such as remotely piloted aircraft systems and can be a part of artificial intelligence in navigation and control systems.

Authors and Affiliations

Volodymyr Kharchenko, Alexander Kukush, Nataliia Kuzmenko, Ivan Ostroumov

Keywords

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  • EP ID EP459676
  • DOI 10.18372/2306-1472.71.11741
  • Views 135
  • Downloads 0

How To Cite

Volodymyr Kharchenko, Alexander Kukush, Nataliia Kuzmenko, Ivan Ostroumov (2017). PROBABILISTIC APPROACH TO OBJECT DETECTION AND RECOGNITION FOR VIDEOSTREAM PROCESSING. Вісник Національного Авіаційного Університету, 71(2), 8-14. https://europub.co.uk/articles/-A-459676