Comparative analysis of background subtraction algorithms in the task of recognizing and identifying people in a video stream | Научно-инновационный портал СФУ

Comparative analysis of background subtraction algorithms in the task of recognizing and identifying people in a video stream

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 2020 International Conference on Information Technology in Business and Industry, ITBI 2020

Год издания: 2020

Идентификатор DOI: 10.1088/1742-6596/1661/1/012041

Аннотация: The article is devoted to one of the most urgent tasks for today: preprocessing video material in the process of recognizing and identifying people in a video stream. The authors of this article conducted a study, which consists in comparing the results of several algorithms for subtracting the background on various input video materials (from the office and the minimum concentration of people, to the dining room in which there are up to ten or more people). The data obtained during the analysis of the algorithms is compared (such data are the number of frames processed per second, and the average load of the computer's central processor). The most efficient algorithms that coped with the task most quickly, accurately and with the least expenditure of resources, were identified, as well as those that coped with the task the worst. © Published under licence by IOP Publishing Ltd.

Ссылки на полный текст

Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1661, Is. 1

Номера страниц: 12041

ISSN журнала: 17426588

Издатель: IOP Publishing Ltd

Авторы

  • Idimechev I.A. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation)
  • Mikhalev A.S. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation)
  • Goponenko A.A. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation)
  • Stavenko S.S. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation)
  • Kukartsev V.V. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Tynchenko V.S. (Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)

Вхождение в базы данных

Информация о публикациях загружается с сайта службы поддержки публикационной активности СФУ. Сообщите, если заметили неточности.

Вы можете отметить интересные фрагменты текста, которые будут доступны по уникальной ссылке в адресной строке браузера.