VR Streaming QoE Measurement via Source-Client Frame Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Virtual reality (VR) streaming experiences are negatively impacted by network impairments such as latency, packet loss, and jitter, making it difficult to assess the quality-of-experience (QoE) for users, and severe impairments can cause uncomfortable side effects like motion sickness.
Innovation Solution
A method and system that generate a Quality-of-Experience (QoE) metric by comparing a client-side VR stream capture with induced network impairments to a source VR stream capture without impairments, using frame-by-frame analysis to quantify the degree of degradation, allowing for identification of optimal network locations to maximize user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network impairments are induced to test VR streaming, then the realism of network conditions is improved, but the quality-of-experience for users deteriorates
Solution Approach 1:
The system segments the VR streaming evaluation into two distinct components: a source capture representing ideal conditions and a client-side capture representing impaired conditions. This segmentation allows independent analysis of network impairment effects without permanently degrading user experience, as each component can be evaluated separately through frame-by-frame comparison.
Solution Approach 2:
The system creates a copy of the VR stream at the source end (source capture) that represents ideal streaming conditions. This copy is then compared against the client-side capture that experiences induced network impairments. The copying approach enables realistic testing of impaired conditions while preserving the original high-quality source for reference and comparison.
2Measurement precision
If frame-by-frame comparison is performed to measure QoE, then the measurement precision of degradation is improved, but the computational complexity increases
Solution Approach 1:
The system performs preliminary actions by capturing and storing both source and client-side VR streams in advance before conducting the actual comparison. The source capture is generated beforehand under ideal conditions, and the client-side capture is recorded during impaired streaming. This preliminary capture approach allows the intensive frame-by-frame comparison to be performed on pre-recorded data rather than in real-time, reducing computational complexity while maintaining high measurement precision.
3Adaptability or versatility
If VR content is streamed over network to enable remote access, then the adaptability of VR delivery is improved, but the reliability of user experience deteriorates due to network impairments
Solution Approach 1:
The system establishes a feedback mechanism by comparing the source capture with the client-side capture and generating a QoE metric that quantifies degradation. This feedback information about network impairment effects can then be used to adjust streaming parameters, select optimal delivery locations, or implement corrective measures to improve reliability while maintaining the adaptability of remote VR content delivery.
Data Source
AI summary
Measuring quality-of-experience (QoE) for virtual reality (VR) streaming content is disclosed. A network computing device receives a client-side VR stream capture and a client pose data set that are generated by a client computing device based on a VR content and one or more induced network impairments (e.g., latency, packet loss, and/or jitter, as non-limiting examples). Using the same VR content and the client pose data set, the network computing device generates a source VR stream capture that is not subjected to the one or more induced network impairments. The network computing device performs a frame-by-frame comparison of the client-side VR stream capture and the source VR stream capture. Based on the frame-by-frame comparison, the network computing device generates a QoE metric that indicates a degree of degradation of the client-side VR stream capture relative to the source VR stream capture.