Shared Virtual Environment Sensor Fidelity for Lower Tracking Power
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High power consumption and inefficient battery life in devices due to simultaneous running of multiple tracking algorithms for detailed features in shared virtual environments, especially when these features are not visible or discernible to others, leading to unnecessary power usage.
Innovation Solution
A system that adjusts sensor usage based on contextual factors within applications, such as user proximity and activity, to align output fidelity with the fidelity requirements of the shared virtual environment, optimizing resource efficiency and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high fidelity tracking algorithms are run simultaneously to create realistic avatar representations, then the realism and detail of user representations are improved, but the power consumption increases significantly reducing battery life
Solution Approach 1:
The system dynamically adjusts tracking fidelity based on contextual factors such as user proximity, avatar visibility, and interaction importance. When users are far apart or avatars are not the main focus, the system reduces tracking precision to conserve battery power. This dynamic adaptation resolves the contradiction by making tracking fidelity variable rather than constant, matching resource usage to actual need.
Solution Approach 2:
Different tracking fidelity levels are applied to different users and avatars based on their relevance to the current interaction. The system identifies which users require high-fidelity tracking (e.g., close proximity, active speaking) and which can use lower fidelity (e.g., distant users, passive listeners). This selective application of quality resolves the contradiction by concentrating computational resources where they provide the most value.
2Measurement precision
If detailed tracking features are continuously monitored to enhance user representation, then the quality of avatar representation is improved, but unnecessary power is consumed when features are not visible or discernible to others
Solution Approach 1:
The system continuously monitors contextual feedback including virtual distance between users, avatar visibility on other screens, and current interaction focus. Based on this feedback, it adjusts tracking algorithms in real-time. When feedback indicates that detailed features are not visible or relevant (e.g., user is far away, avatar is small in view), the system reduces tracking intensity to eliminate unnecessary power consumption while maintaining quality when needed.
Solution Approach 2:
Instead of continuously applying full-fidelity tracking to all users, the system applies partial tracking action only where necessary. It identifies the minimum required tracking fidelity for each user based on visibility and interaction context, avoiding excessive processing for users whose avatars are not currently discernible to others, thus reducing wasted energy.
3Adaptability or versatility
If multiple tracking algorithms run simultaneously for all users, then comprehensive user representation is achieved, but device resources are inefficiently utilized
Solution Approach 1:
The system segments the user base into different groups based on their current interaction context, proximity, and visibility. Different tracking algorithms and fidelity levels are assigned to different segments. This segmentation allows comprehensive representation for users who need it while using simpler, more efficient algorithms for users who don't, thereby improving overall resource efficiency without sacrificing necessary adaptability.
Data Source
AI summary
A system for optimizing sensor data processing in a shared virtual environment can include a processor and a memory storing instructions. The instructions can be executable by the processor to cause the processing circuitry of the processor to receive context data indicative of a virtual environment interaction, determine a fidelity requirement for sensor data based on the context data, and adjust sensor data processing parameters to align an output fidelity with the fidelity requirement.