Real-time video transmission adaptive forward error correction method and system based on deep learning

A real-time video and deep learning technology, applied in neural learning methods, biological neural network models, selective content distribution, etc., can solve problems such as inability to protect data, ignoring the complex relationship between history and future, and improve quality and The effect of channel utilization, ensuring feasibility, and improving coding efficiency
CN111629232AInactive Publication Date: 2020-09-04PEKING UNIV
3 Cites 5 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
PEKING UNIV
Publication Date
2020-09-04
Estimated Expiration
Not applicable · inactive patent

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a real-time video transmission adaptive forward error correction method and system based on deep learning, which can predict the network condition change trend in a future period of time when the network condition fluctuates and adaptively change the parameters of a forward error correction algorithm so as to ensure the transmission quality of real-time video data. The method mainly contributes to (1) learning a change rule of a network condition through a neural network model so as to predict a future network packet loss condition for a past network condition; and (2)adding a counter module to the model, and converting model output from a network feature sequence into a network packet loss rate, so that the model output is simplified, and the prediction accuracy is improved; and (3) setting an interval between past and future time periods during neural network learning and prediction, so that the problem of real-time feedback of network conditions is solved, and the neural network model can be used for real-time prediction in a real-time video transmission system.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention belongs to the technical field of network streaming media transmission, and in particular relates to a real-time video transmission method and system for realizing network self-adaptive forward error correction so as to reduce transmission packet loss. Background technique

[0002] Live video streaming has become increasingly common in recent years. Online video streaming is expected to account for 82% of internet traffic by 2022. At the same time, more and more online videos will be in the form of live streaming, and real-time video communication is attracting more and more attention from users and researchers. However, packet loss is a critical issue in real-time video communication, as it causes distortion and decoding errors, thereby degrading the user's quality of experience. The International Telecommunication Union (ITU) standard limits the one-way delay to less than 200ms for real-time communication applications such as video co...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More