Video Quality Assessment Using Transport Header Analysis
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Solution Overview
Problem
Existing methods for predicting the effect of packet loss on video transmission quality are limited by the need for access to the video payload, which is often encrypted, making accurate estimation difficult, especially when frames span multiple packets and factors like frame type, packet loss position, and endpoint behavior are not adequately considered.
Innovation Solution
A method that estimates video quality degradation using only the media transport protocol header, employing weighted counters to account for packet loss impact based on frame size and position, and optimizing weighting coefficients for specific video endpoints, thus being independent of payload encryption and considering various frame types and endpoint behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If access to video payload is used for quality assessment, then measurement precision is improved, but ease of operation deteriorates due to encryption requirements
Solution Approach 1:
The invention extracts the necessary quality assessment information from the packet header fields (sequence numbers, timestamps, frame type indicators) rather than requiring access to the encrypted video payload. This extraction approach maintains measurement capability while eliminating the operational barrier of payload decryption.
Solution Approach 2:
The packet header serves as an intermediary that carries sufficient information for quality assessment without requiring direct access to the encrypted payload. The header fields act as a mediator between the unencrypted transport layer and the quality assessment function, enabling measurement without breaking encryption.
2Device complexity
If packet loss impact is assessed without considering frame type and position, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The invention applies local quality assessment by differentiating the impact of packet loss based on frame type (I-frames, P-frames, B-frames) and packet position within a frame. Different weighting factors are applied to different frame types and loss positions, reflecting the local importance of different parts of the video stream to overall quality.
Solution Approach 2:
The assessment model dynamically changes parameters (weighting factors) based on frame type and packet position. I-frames receive higher weighting than P-frames, and packets containing frame headers or critical data receive higher weighting than other packets, allowing precise quality prediction without excessive complexity.
3Adaptability or versatility
If generic packet loss model is used, then adaptability is improved, but measurement precision deteriorates due to endpoint-specific variations
Solution Approach 1:
The invention implements a dynamic weighting system where the importance weights for different frame types and packet positions can be adjusted based on the specific video endpoint and codec being assessed. This allows the generic model structure to adapt to endpoint-specific characteristics, maintaining both versatility and precision.
Data Source
AI summary
The present invention relates to the problem of estimating the effect of packet transmission impairments, including packet loss, on the subjective quality of a video transmission where frames of data relating to the same video frame or field are permitted to span more than one packet. The invention provides a method of assessing quality of a video signal comprising a sequence of video frames received via a packet switched network using a parameter which is a weighted sum of two counters where the first counter is incremented in dependence of the total number of packets in frames determined to have been received with one or more lost packets and the second counter is incremented in dependence of the number of packets following the first lost packet in each frame and the lost packet itself.