title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼Ð½Ð¾Ð³Ð¾ÑÐ»Ð¾Ð¹Ð½Ð¾Ð¹ ÑÑ ÐµÐ¼Ñ ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð²Ð¸Ð´ÐµÐ¿Ð¾ÑÐ¾ÐºÐ°
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: Development of a multilayer semantic coding scheme for video stream
Creators: name: ÐÐ¾Ð±ÑÐ¶ÐµÐ², 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: 2024
Subjects: ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¸Ð´ÐµÐ¾Ð¿Ð¾ÑÐ¾ÐºÐ°
ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð°Ñ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐ°
ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¸Ð´ÐµÐ¾ Ð´Ð»Ñ Ð¼Ð°ÑÐ¸Ð½
Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÐµ ÐºÐ¾Ð´ÐµÐºÐ¸
Ð¼Ð½Ð¾Ð³Ð¾ÑÐ»Ð¾Ð¹Ð½ÑÐµ ÑÑ ÐµÐ¼Ñ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ
video coding
image feature coding
deep learning
machine analytics
video coding for machines
neural network codecs
multilayer coding schemes

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¼Ð½Ð¾Ð³Ð¾ÑÐ»Ð¾Ð¹Ð½Ð¾Ð¹ ÑÑÐµÐ¼Ñ ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð²Ð¸Ð´ÐµÐ¾Ð¿Ð¾ÑÐ¾ÐºÐ° Ð´Ð»Ñ ÑÑÐµÐ½ Ð´Ð¾ÑÐ¾Ð¶Ð½Ð¾Ð³Ð¾ Ð²Ð¸Ð´ÐµÐ¾Ð½Ð°Ð±Ð»ÑÐ´ÐµÐ½Ð¸Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¾ÑÐµÐ½ÐºÐµ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÐµÑ ÑÐ°Ð±Ð¾ÑÑ. ÐÑÐ¾Ð²ÐµÐ´ÑÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² Ðº ÑÐ¶Ð°ÑÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð¸ Ð²Ð¸Ð´ÐµÐ¾, ÑÑÐ¾ÑÐ¼ÑÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÑÐµÐ±Ð¾Ð²Ð°Ð½Ð¸Ñ Ðº ÑÑÐµÐ¼Ðµ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½Ð¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸. ÐÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð¾ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð¹ Ð¼Ð½Ð¾Ð³Ð¾ÑÐ»Ð¾Ð¹Ð½Ð¾Ð¹ ÑÑÐµÐ¼Ñ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð²Ð¸Ð´ÐµÐ¾Ð¿Ð¾ÑÐ¾ÐºÐ° Ð¸ ÑÑÐ½ÐºÑÐ¸Ð¸ Ð¿Ð¾ÑÐµÑÑ Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð´ÐµÐºÐ°. Ð¢Ð°ÐºÐ¶Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð°Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð´ÐµÐºÐ°, Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½Ð¾Ð¹ ÑÑÐµÐ¼Ñ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ¾Ð´ÐµÐºÐ¾Ð² Ð´Ð»Ñ ÑÐ¶Ð°ÑÐ¸Ñ Ð²Ð¸Ð´ÐµÐ¾ Ð½Ð° ÑÐ·ÑÐºÐµ Python. ÐÐ¾ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÑÐµÐ¼Ñ ÐºÐ¾Ð´Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð°Ð½Ñ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÑÐ¶Ð°ÑÐ¸Ñ Ð´Ð»Ñ Ð·Ð°Ð´Ð°Ñ Ð´ÐµÑÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð²ÑÐ±ÑÐ°Ð½Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð°Ð»ÑÐ½ÑÐµ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð³Ð¾ ÐºÐ¾Ð´ÐµÐºÐ°.
description: This work is devoted to the realization of a multilayer semantic coding scheme for video stream for road surveillance scenes, as well as to the evaluation of its efficiency. The existing approaches to image and video compression are analyzed, and the requirements to the coding scheme for solving the problem are formulated. The description of the developed multilayer video stream coding scheme and loss function for neural network codec training is presented. Also, the program realization of training of neural network codec, the proposed coding scheme and testing of codecs for video compression in Python language is developed. Based on the results of testing the coding scheme, the compression efficiency for detection and recognition tasks is evaluated, and the optimal parameters of the neural network codec are selected.