Mixed Reality Image Overlay Transparency Adjustment
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Solution Overview
Problem
Current image processing methods for mixed reality (MR) are cumbersome for users, requiring frequent switching between image displays and manual adjustments of transparency parameters, making it difficult to extract object regions accurately and efficiently.
Innovation Solution
An image processing method that captures a shot image, extracts a predetermined region, generates a virtual image based on a transparency parameter, combines it with the shot image excluding the region, and displays the combined image with dynamically changing transparency, allowing for easy parameter adjustment and region distinction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of transparency parameters is used, then parameter precision can be achieved, but operation complexity increases and user efficiency decreases
Solution Approach 1:
The system automatically adjusts the transparency parameter based on the extracted object region, eliminating the need for manual user adjustment. The transparency value is computed self-service style from the region extraction results, directly resolving the contradiction by making the system intelligent rather than requiring precise manual input from the user.
Solution Approach 2:
The transparency parameter is dynamically changed based on the extracted object region characteristics. Instead of manual parameter setting, the system automatically determines the transparency value from the region extraction data, allowing precise parameter control without manual intervention.
2Measurement precision
If frequent switching between image displays is required, then parameter adjustment accuracy can be improved, but time consumption increases
Solution Approach 1:
The system automatically determines the transparency parameter from the extracted object region without requiring users to switch between displays for adjustment. The parameter is computed self-service style, eliminating time-consuming manual adjustment iterations.
Solution Approach 2:
The transparency parameter is pre-computed based on the extracted object region before final image composition. This preliminary determination of parameters eliminates the need for repeated display switching and adjustment, saving user time.
3Measurement precision
If manual region extraction is used, then extraction accuracy can be achieved, but operation complexity increases
Solution Approach 1:
The system performs automatic region extraction based on color information and luminance thresholds without requiring manual user operations. The extraction process serves itself by automatically identifying object regions, eliminating complex manual extraction steps while maintaining accuracy.
Solution Approach 2:
Manual mechanical region extraction operations are replaced with automated image processing algorithms. The system uses color space conversion and threshold-based extraction to automatically identify regions, substituting manual operations with computational methods.
Data Source
AI summary
A CG image having a transparency parameter is superimposed on a shot image, which is an image picked up by an image-pickup device, to obtain a combined image. The combined image is displayed in a combined-image-display region. In the combined image, a mask region of the CG image is set based on parameter information used to extract a region of a hand. The transparency parameter of the CG image is set based on a ratio of the size of the region of the CG image excluding the mask region to the size of the shot image. By checking the combined image, which is displayed in the combined-image-display region, the user can set the parameter information by a simple operation.