title: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÑÐ²ÑÑÑÐ¾ÑÐ½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ° Ñ ÑÐµÐ»ÑÑ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ° Ð¿Ð¾ Ð²Ð¸Ð´ÐµÐ¾Ð·Ð°Ð¿Ð¸ÑÐ¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Research of the efficiency of convolutional neural networks and tracking algorithms with the purpose of determing object's speed by video record
Creators: name: Ð£Ð¾Ð³Ð¸Ð½ÑÐ°-ÐÑÑÐ¾ÑÐ°Ñ, ÐÐ»ÐµÐºÑÐ°Ð½Ð´Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð´ÐµÑÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
ÑÑÐµÐºÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
ÑÐºÐ¾ÑÐ¾ÑÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
computer vision
object detection
object tracking
object speed

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description: In this paper, approaches for the comparison and subsequent tracking of objects by video recording are considered in order to determine the speed of their movement using convolutional neural networks and matching algorithms in real time. The features of the architectures of convolutional neural networks suitable for detecting objects in a video stream are presented, and an assessment of their applicability for solving the problem is given. Algorithms for tracking objects are considered. Their features are highlighted and the limits of applicability of these algorithms are determined. The requirements for the experimental environment are determined in order to approximate the real-time conditions, the implementation of the environment for the experiment is carried out. On the basis of the experiment, results were obtained on the behavior of tracking algorithms and their effectiveness in solving the problem of determining the speed of an object from video recording.