Metaverse Video Rendering Error Detection With Simulated Devices
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Solution Overview
Problem
Existing methods for testing software applications in metaverse environments are labor-intensive, time-consuming, and prone to human errors due to the need for manual inspection across multiple user devices, with no intelligent error resolution systems available.
Innovation Solution
A system utilizing a rendering manager that runs the application on simulated user devices to detect and resolve errors by comparing rendered views with expected patterns, applying known solutions to correct detected issues, and optimizing source code to improve compatibility and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual visual inspection is used to test software application rendering across multiple user devices, then testing can be performed on real-world devices, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent creates simulated user devices that replicate real-world devices (smartphones, tablets, wearables) with their specific hardware configurations, display characteristics, and processing capabilities. These simulations allow automated visual inspection of rendered virtual environments without requiring physical devices, thereby improving testing efficiency while maintaining reliability through accurate replication of device behaviors.
Solution Approach 2:
The patent replaces manual visual inspection with automated computer-based detection systems. The simulated user devices automatically capture rendered frames, compare them against expected patterns, and identify rendering errors without human intervention. This substitution of mechanical manual inspection with automated digital comparison significantly improves productivity while maintaining or enhancing testing accuracy.
2Reliability
If manual visual inspection is used to detect rendering errors, then human judgment can identify visual issues, but the process is prone to human errors and lacks consistency
Solution Approach 1:
The patent implements automated feedback mechanisms where the simulated user devices automatically compare rendered frames against expected view patterns stored in memory. The system provides immediate feedback on rendering quality by detecting mismatches between actual and expected visual outputs, ensuring consistent and reliable error detection without the variability inherent in manual inspection.
Solution Approach 2:
The simulated user devices autonomously perform the entire testing process including capturing rendered frames, comparing against expected patterns, identifying errors, and even resolving issues through self-correction mechanisms. This self-service automation eliminates human error and maintains consistent detection accuracy across all testing scenarios.
3Reliability
If testing is performed on real-world user devices, then actual device performance can be evaluated, but processing resources are consumed and errors must be resolved after detection
Solution Approach 1:
The patent performs all testing and error detection actions preliminarily on simulated user devices before the software application is deployed to real-world devices. By conducting rendering tests, visual inspection, and error identification in advance on simulations, the system validates performance and resolves issues proactively, eliminating the need for resource-intensive post-detection resolution on actual hardware.
Solution Approach 2:
The simulated user devices replicate the hardware specifications, display characteristics, and processing capabilities of real devices, allowing performance validation without consuming actual processing resources. The simulations mirror real device behaviors while operating within a more efficient computational environment, enabling thorough performance testing with lower resource consumption.
4Adaptability or versatility
If a single software application is designed to be compatible with multiple user device types, then versatility is achieved, but testing complexity increases due to the need to verify rendering on each device
Solution Approach 1:
The patent creates a universal testing framework where simulated user devices can represent multiple device types (smartphones, tablets, wearables) within a single system. The same simulation infrastructure and automated testing processes can evaluate rendering compatibility across all device types, reducing testing complexity while maintaining comprehensive multi-device verification for versatile applications.
Solution Approach 2:
The patent segments the testing process into modular components where each simulated user device can be independently configured and tested. The rendering manager divides the testing workload by creating separate simulated devices for different platforms, allowing parallel testing of the software application on multiple device types simultaneously, thereby reducing overall testing complexity through systematic organization.
Data Source
AI summary
A system includes a memory and a processor coupled to the memory. The processor runs a software application on a simulated user device to render a virtual environment on the simulated user device. In response to detecting that the software application has rendered a video clip in the virtual environment, the processor converts the video clip into metadata. The processor compares a first metadata associated with a first frame of the video clip with a second metadata associated with at least one second frame of the video clip before or after the first frame. In response to determining that the first frame and the second frame do not conform to a pre-configured transition, the processor determines that an error has occurred in relation to rendering the video clip. The processor obtains a solution corresponding to the error and applies the solution to the software application to resolve the detected error.