Remote Desktop Frame Quality Benchmark via Timestamp Video
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Solution Overview
Problem
Measuring display quality in a remote desktop environment is challenging due to the need for accurate comparison of user experience between client and server sides, particularly in terms of frame rate and image quality, which is affected by network latency and bandwidth.
Innovation Solution
A method involving a benchmark server and client application that uses a timestamp video to calculate relative frame rate and overall image quality scores by comparing frames on both sides, with additional weighting for bad blocks and network latency considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frame rate and image quality are measured in remote desktop environments, then display quality evaluation is improved, but measurement precision deteriorates due to network latency and bandwidth variations
Solution Approach 1:
The patent introduces a timestamp video as an intermediary test content that is played on the server and captured on both server and client sides. This intermediary allows indirect measurement of display quality by comparing timestamps in captured frames, thereby avoiding direct measurement challenges caused by network latency and bandwidth variations.
Solution Approach 2:
The patent creates copies of the timestamp video content on both server and client sides through screen capture. By comparing these captured frame copies, the system can evaluate display quality without directly measuring the transmitted video signal, thus overcoming network-related measurement inaccuracies.
2Measurement precision
If accurate frame rate comparison is performed between client and server, then display quality metric is improved, but device complexity increases due to synchronization requirements
Solution Approach 1:
The timestamp video contains embedded temporal information that enables self-synchronization. The timestamps embedded in the video content itself allow the system to automatically determine frame correspondence without requiring external synchronization signals or complex coordination mechanisms between server and client.
Solution Approach 2:
The timestamp video is prepared in advance with embedded timestamps that encode temporal information. This preliminary encoding of time information into the test content allows for straightforward frame rate comparison when the video is played and captured, eliminating the need for complex real-time synchronization during measurement.
3Measurement precision
If image quality is evaluated by comparing client and server frames, then user experience assessment is improved, but loss of information occurs due to network compression and latency
Solution Approach 1:
The timestamp video serves as an intermediary that is specifically designed to be resilient to network compression. By embedding distinctive timestamps in the test content, the system can identify and compare corresponding frames even when network compression and latency cause variations in the transmitted video data.
Solution Approach 2:
The timestamp video utilizes distinct visual patterns and color variations in the timestamp display that make it easily distinguishable and comparable. These visual changes in the timestamp content allow for reliable frame matching and quality assessment even when network compression alters the overall video appearance.
Data Source
AI summary
A method is provided to measure an overall image quality score for a remote desktop on a first computer and accessed from a second computer. The method includes playing a video timestamp on the remote desktop at the first computer where the video timestamp includes unique timestamps, screen capturing first computer frames of the remote desktop at the first computer and second computer frames of the remote desktop at the second computer at the same time, determining a frame image quality score for each second computer frame by comparing the client screen to a corresponding baseline first computer frame, and determining the overall image quality score for the remote desktop from frame image quality scores of the second computer frames.