Stereoscopic Conversion Using Disparity and Coverage Maps
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Solution Overview
Problem
Current methods for converting 2D images to 3D stereoscopic images are inefficient and often fail to accurately translate transparency and depth information, leading to incomplete or distorted secondary views.
Innovation Solution
The method involves generating a primary view image and calculating disparity values between the primary and secondary camera perspectives, using these values to reposition pixels and create a secondary view image, while also applying coverage maps to ensure accurate transparency and depth translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current methods are used for converting 2D images to 3D stereoscopic images, then the conversion process is simple, but the accuracy of transparency and depth information is poor
Solution Approach 1:
The patent segments the image processing into distinct stages: generating a primary view image, calculating disparity values for each pixel, applying coverage maps to preserve transparency information, and synthesizing the secondary view image. This segmentation allows each stage to be optimized independently, improving overall accuracy while managing complexity.
Solution Approach 2:
The patent performs preliminary actions by first generating a primary view image and calculating disparity values before creating the secondary view. Coverage maps are prepared in advance to ensure transparency information is preserved during the disparity-based pixel repositioning process.
2Manufacturing precision
If complex processing methods are applied to ensure accurate transparency and depth translation, then the quality of stereoscopic image is improved, but the processing requirements increase
Solution Approach 1:
The patent extracts coverage information from the primary view image to create coverage maps that are applied during secondary view generation. This extraction approach preserves transparency and depth information without requiring complete reprocessing of the entire image, thereby maintaining quality while reducing processing requirements.
3Reliability
If disparity values are calculated for all pixels to create accurate secondary view, then the completeness of stereoscopic image is improved, but the processing time increases
Solution Approach 1:
The patent applies local quality by calculating disparity values and applying coverage maps specifically to regions where transparency and depth information are critical. This localized approach ensures completeness of the stereoscopic image while avoiding unnecessary processing of all pixels, thereby reducing processing time.
Data Source
AI summary
A method performed by one or more processors includes: receiving model data defining a three-dimensional scene; rendering the three-dimensional scene into a primary view image showing the three-dimensional scene from a view of a primary camera; and generating, for each of at least some pixels in the primary view image, a disparity value that defines a disparity between a location of the pixel in the primary view image and an indicated location of the pixel in a secondary view image showing the three-dimensional scene from a view of a secondary camera.