title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼ÐµÑÐ¾Ð´Ð° ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð³ÑÑÐ¿Ð¿Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð°ÑÑÐ¾ÑÐ¾ÑÐ¾ÑÐ½Ð¸Ð¼ÐºÐ¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Implementation of an algorithm for tracking a group of objects on a sequence of aerial photographs
Creators: name: Ð¤Ð¾Ð¼Ð¸Ð½Ð°, ÐÐ»ÐµÐ½Ð°
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: ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ðµ
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ
Ð°ÑÑÐ¾ÑÐ¾ÑÐ¾ÑÑÐµÐ¼ÐºÐ°
Ð¾ÑÑÐ»ÐµÐ¶Ð¸Ð²Ð°Ð½Ð¸Ðµ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
yolov4
deepsort
tracking
detection
aerial photography
neural networks

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð°Ð½Ð°Ð»Ð¸Ð·Ñ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð³ÑÑÐ¿Ð¿Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð¸ Ð¸Ñ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ. ÐÑÐµÐ´Ð¼ÐµÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â Ð¾Ð±ÑÐµÐºÑÑ, Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð°ÑÑÐ¾ÑÐ¾ÑÐ¾ÑÑÐµÐ¼ÐºÐ¸ Ñ ÐºÐ°Ð¼ÐµÑ, ÑÑÑÐ°Ð½Ð¾Ð²Ð»ÐµÐ½Ð½ÑÑ Ð½Ð° Ð»ÐµÑÐ°ÑÐµÐ»ÑÐ½Ð¾Ð¼ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐµ. ÐÐ¾ÑÐ»Ðµ Ð¾Ð±Ð·Ð¾ÑÐ° ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð±ÑÐ»Ð° Ð²ÑÐ±ÑÐ°Ð½Ð° Ð¾Ð¿ÑÐ¸Ð¼Ð°Ð»ÑÐ½Ð°Ñ Ñ ÑÐ¾ÑÐºÐ¸ Ð·ÑÐµÐ½Ð¸Ñ ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ Ð¸ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ YOLOv4-tiny. ÐÐ¾ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼ Ð¾Ð±Ð·Ð¾ÑÐ° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ Ð±ÑÐ»Ð¸ Ð²ÑÐ±ÑÐ°Ð½Ñ ÑÑÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°: Ð¼ÐµÑÐ¾Ð´ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸Ð½Ð´ÐµÐºÑÐ° ÐÐ°ÐºÐºÐ°ÑÐ°, SORT, DeepSORT. ÐÐ±ÑÐ°Ð±Ð¾ÑÐºÑ ÑÐ»ÑÑÐ°ÐµÐ² Ð¿ÑÐ¾Ð¿ÑÑÐµÐ½Ð½ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð±ÑÐ»Ð¾ ÑÐµÑÐµÐ½Ð¾ Ð²ÑÐ¿Ð¾Ð»Ð½ÑÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ¸Ð»ÑÑÑÐ° ÐÐ°Ð»Ð¼Ð°Ð½Ð°, Ð²ÑÐ¾Ð´ÑÑÐµÐ³Ð¾ Ð² ÑÑÑÑÐºÑÑÑÑ SORT Ð¸ DeepSORT, Ð¸ Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð³Ð¾ Ð±Ð¸Ð½Ð°ÑÐ½Ð¾Ð³Ð¾ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ°. ÐÐ»Ñ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð½Ð°Ð¸Ð±Ð¾Ð»ÐµÐµ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÐµÐ½Ð½ÑÐµ Ð´Ð»Ñ Ð¾ÑÑÐ»ÐµÐ¶Ð¸Ð²Ð°Ð½Ð¸Ñ Ð¼ÐµÑÑÐ¸ÐºÐ¸ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ Ð¸ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸. ÐÐµÑÐ¾Ð´ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸Ð½Ð´ÐµÐºÑÐ° ÐÐ°ÐºÐºÐ°ÑÐ° Ð¾Ð¶Ð¸Ð´Ð°ÐµÐ¼Ð¾ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ°Ð¼ÑÐ¼ Ð±ÑÑÑÑÑÐ¼, Ð½Ð¾ ÑÑÑÑÐ¿Ð°ÐµÑ Ð² ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ð´ÑÑÐ³Ð¸Ð¼ Ð¸ ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸Ð·ÑÐµÑÑÑ Ð±Ð¾Ð»ÑÑÐ¸Ð¼ ÑÐ¸ÑÐ»Ð¾Ð¼ Ð¿ÐµÑÐµÐºÐ»ÑÑÐµÐ½Ð¸Ð¹ Ð¸Ð´ÐµÐ½ÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ°. ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ DeepSORT Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÑ Ð´ÐµÑÐºÑÐ¸Ð¿ÑÐ¾Ñ Ð²Ð½ÐµÑÐ½ÐµÐ³Ð¾ Ð²Ð¸Ð´Ð°, Ð¸Ð·Ð²Ð»ÐµÐºÐ°ÐµÐ¼ÑÐ¹ Ð¾ÑÐ´ÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ð¹ ÑÐµÑÑÑ, ÑÑÐ¾ Ð¿Ð¾Ð²ÑÑÐ°ÐµÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ñ Ñ SORT Ð¸ ÑÐ¼ÐµÐ½ÑÑÐ°ÐµÑ ÑÐ¸ÑÐ»Ð¾ Ð¿ÐµÑÐµÐºÐ»ÑÑÐµÐ½Ð¸Ð¹ Ð¸Ð´ÐµÐ½ÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ°, Ð½Ð¾ Ð² ÑÐ¾ Ð¶Ðµ Ð²ÑÐµÐ¼Ñ Ð·Ð°Ð¼ÐµÐ´Ð»ÑÐµÑ ÑÐ°Ð±Ð¾ÑÑ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ, Ð¸ Ð² ÑÐ²ÑÐ·Ð¸ Ñ ÑÐµÐ¼, ÑÑÐ¾ Ð°Ð»Ð³Ð¾-ÑÐ¸ÑÐ¼ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÑ, Ð²ÑÐµÐ¼Ñ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð±ÑÑÑÑÐ¾ ÑÐ°ÑÑÐµÑ Ñ ÑÐ²ÐµÐ»Ð¸ÑÐµÐ½Ð¸ÐµÐ¼ ÑÐ¸ÑÐ»Ð° Ð¾Ð±ÑÐµÐºÑÐ¾Ð². ÐÑÐµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð½ÑÐµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¼Ð¾Ð³ÑÑ Ð²ÑÐ¿Ð¾Ð»Ð½ÑÑÑÑÑ Ð² ÑÐµÐ¶Ð¸Ð¼Ðµ ÑÐµÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð²ÑÐµÐ¼ÐµÐ½Ð¸, Ð° Ð·Ð½Ð°ÑÐ¸Ñ, Ð¾Ð½Ð¸ Ð¼Ð¾Ð³ÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑÑÑ Ð¿ÑÐ¸ Ð¾ÑÑÐ»ÐµÐ¶Ð¸Ð²Ð°Ð½Ð¸Ð¸ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð°ÑÑÐ¾ÑÐ¾ÑÐ¾ÑÐ½Ð¸Ð¼ÐºÐ¾Ð², Ð¾Ð´Ð½Ð°ÐºÐ¾ Ð½Ð°Ð¸Ð±Ð¾Ð»ÑÑÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÐµÑ DeepSORT.
description: This work is devoted to the analysis of several algorithms for tracking a group of objects and their comparison. The subject of research is objects obtained using aerial photography from cameras installed on an aircraft. After reviewing the existing detection methods, the YOLOv4-tiny neural network, optimal in terms of speed and accuracy, was chosen. Based on the results of a review of various tracking methods, three algorithms were selected for comparison: the method based on the Jaccard index, SORT algorithm, and DeepSORT algorithm. I decided to process the cases of missed detection results using the Kalman filter included in the SORT and DeepSORT structures and an additional binary classifier. For comparison, we used the most common tracking metrics for assessing speed and accuracy. The method based on the Jaccard index is, as expected, the fastest, but it is inferior in accuracy to others and is characterized by many identifier switches. The DeepSORT algorithm uses an appearance descriptor retrieved by a separate convolutional network, which improves accuracy compared to SORT and reduces the number of ID switches, but at the same time slows down the execution of the program, and since the algorithm uses a neural network, the processing time is fast grows with an increase in the number of objects. All the considered algorithms can work in real time, which means that the algorithms can be used to track objects in a sequence of aerial photographs, however, DeepSORT shows the highest accuracy.