VR Streaming Latency Adaptation via Head Motion Quantifier
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In virtual reality streaming environments, latency can significantly impact the quality of experience for users, leading to visual discontinuities and an unpleasant experience, especially when users move their heads rapidly.
Innovation Solution
A computing device dynamically streams virtual reality content to a head-mounted display device by determining a latency value based on the round-trip time of data and a head motion quantifier associated with the content. Based on these values, the system determines a quality of experience level and performs actions to optimize the streaming, such as informing the user or redirecting the content to a different server with lower latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual reality content is streamed over a network to an HMDD, then the user can access immersive VR content, but latency negatively impacts the quality of experience
Solution Approach 1:
The system pre-determines a quality of experience level based on predicted latency and head motion quantifier before actually streaming the content. This preliminary assessment allows the system to prepare appropriate quality settings and inform users in advance about the expected experience quality, rather than reacting to latency issues after they occur.
Solution Approach 2:
The system provides feedback to the user about the determined quality of experience level, allowing users to make informed decisions about whether to proceed with the VR content. This feedback mechanism creates a loop where latency predictions directly influence user awareness and system adjustments.
2Reliability
If the system determines quality of experience level based on latency and head motion, then visual discontinuities are minimized, but the system complexity increases
Solution Approach 1:
The system segments the quality assessment into distinct components: determining latency value, determining head motion quantifier, and combining these to determine quality of experience level. This segmentation allows each component to be handled independently with specialized algorithms, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The system performs preliminary determination of quality of experience level before content delivery, using pre-calculated latency values and head motion quantifiers. This preliminary action simplifies the real-time streaming process by having quality parameters ready in advance, reducing the computational burden during actual content delivery.
3Adaptability or versatility
If the system dynamically adjusts streaming based on head movements, then the immersive experience is enhanced, but the data transmission requirements increase
Solution Approach 1:
The system dynamically determines quality of experience level based on real-time or predicted head motion quantifiers and latency values. This dynamic adjustment allows the streaming quality to adapt to user behavior, providing higher quality when head motion is low and lower quality when head motion is high, thereby optimizing data transmission efficiency while maintaining immersive experience.
Data Source
AI summary
Virtual reality content (VR content) streaming based on quality of experience level is disclosed. In response to a request from a head-mounted display device (HMDD) to serve a VR content, a computing device determines a head motion quantifier (HMQ) associated with the VR content. The computing device is configured to dynamically provide to the HMDD imagery from the VR content based on head movements of a user of the HMDD. The computing device determines a latency value associated with a round-trip time of data between the computing device and the HMDD. The computing device determines a quality of experience level of a plurality of different quality of experience levels based on the HMQ and the latency value, and performs an action based on the quality of experience level.