VR Environmental Noise Evaluation via Embedded Image Data Comparison
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Solution Overview
Problem
Virtual Reality (VR) and Augmented Reality (AR) devices face challenges in effectively evaluating environmental noise, which is crucial for selecting appropriate filtering methods to eliminate communication interference and ensuring proper system operation across varying scenarios, including different temperatures and environments.
Innovation Solution
A method that involves obtaining original image data, determining source data, generating comparison data, and calculating a difference value to evaluate environmental noise by using operations such as AND, OR, covariance, or convolution, with the comparison data and source data located in different address regions, allowing for efficient noise evaluation without requiring additional clock cycles or extensive resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If environmental noise evaluation is performed using traditional methods with separate data storage and comparison operations, then measurement precision can be maintained, but device complexity and resource usage increase
Solution Approach 1:
The patent combines the source data and comparison data into a single image data structure, where the comparison data is embedded within the same image matrix as the source data. This merging eliminates the need for separate data storage structures and reduces system complexity while maintaining the ability to perform accurate noise evaluation through differential operations between the embedded datasets.
Solution Approach 2:
The image data structure serves multiple functions simultaneously: it stores both source data and comparison data, enables noise evaluation through differential analysis, and provides a unified framework for environmental assessment. This multi-functionality reduces the need for separate specialized components while maintaining measurement precision.
2Measurement precision
If separate storage locations are used for source data and comparison data, then measurement accuracy is improved, but loss of time and processing efficiency deteriorate
Solution Approach 1:
By embedding comparison data within the same image matrix as source data at different spatial locations, the system enables simultaneous access to both datasets without requiring separate memory operations. This reduces processing time while maintaining the spatial separation needed for accurate differential noise measurement.
3Adaptability or versatility
If comprehensive environmental detection is performed, then adaptability to different scenarios is improved, but use of energy and resource consumption increase
Solution Approach 1:
The image data structure and processing method provide a universal framework that can evaluate environmental noise across diverse scenarios (indoor/outdoor, VR/AR applications) using the same embedded differential approach. This eliminates the need for scenario-specific processing pipelines, reducing energy consumption while maintaining broad adaptability.
Data Source
AI summary
The present disclosure provides a method, apparatus, medium, and electronic device for evaluating environmental noise of device. The method comprises obtaining original image data to be displayed; determining at least part of the original image data to be displayed as source data; obtaining comparison data according to the source data; obtaining a difference value according to the comparison data and the source data; and evaluating environmental noise of device according to the difference value.