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Object detection and tracking in video sequences: formalization, metrics and results

https://doi.org/10.37661/1816-0301-2021-18-1-43-60

Abstract

One of the promising areas of development and implementation of artificial intelligence is the automatic detection and tracking of moving objects in video sequence. The paper presents a formalization of the detection and tracking of one and many objects in video. The following metrics are considered: the quality of detection of tracked objects, the accuracy of determining the location of the object in a frame, the trajectory of movement, the accuracy of tracking multiple objects. Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. Neural network features are included in a composite descriptor that also contains geometric and color features to describe each detected person in the frame. The results of experiments based on the considered criteria are presented, and it is experimentally confirmed that the improvement of the detector operation makes it possible to increase the accuracy of tracking objects. Examples of frames of processed video sequences with visualization of human movement trajectories are presented.

About the Authors

R. P. Bohush
Polotsk State University
Belarus

Rykhard P. Bohush, Cand. Sci. (Eng.), Associate Professor, Head of the Department of Computer Systems and Networks

st. Blokhin, 29, Novopolotsk, 211440



S. V. Ablameyko
Belarusian State University; The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus

Sergey V. Ablameyko, Academician of the National Academy of Sciences of Belarus, Dr. Sci. (Eng.), Professor, Сhief Researcher; Professor of the Faculty of Mechanics and Mathematics

av. Nezaliezhnasti, 4, 220030, Minsk

st. Surganova, 6, Minsk, 220012



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Review

For citations:


Bohush R.P., Ablameyko S.V. Object detection and tracking in video sequences: formalization, metrics and results. Informatics. 2021;18(1):43-60. (In Russ.) https://doi.org/10.37661/1816-0301-2021-18-1-43-60

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ISSN 1816-0301 (Print)
ISSN 2617-6963 (Online)