Mesh-Based Stereo Image Rectification for 3D Display
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Solution Overview
Problem
Conventional methods for producing three-dimensional images require sophisticated and costly camera equipment, such as stereo cameras or synchronized multiple-camera sets, which are limited by cost and complexity, and also demand high photographic skill, making them inaccessible for widespread three-dimensional image production.
Innovation Solution
A method for generating a stereo image pair using a mesh-based transformation function that divides input images into cells, applies an energy minimization function to preserve selected features, and transforms the images to create a stereo image pair suitable for three-dimensional display without the need for specialized equipment or simultaneous image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stereo cameras or synchronized multiple-camera sets are used to produce three-dimensional images, then the quality and intensity of the three-dimensional effect is improved, but the cost of production and device complexity increases significantly
Solution Approach 1:
The patent creates a virtual copy of the stereo camera system through software simulation. Instead of using physical stereo cameras, the invention uses a single camera to capture images and then applies computational algorithms to generate the stereoscopic effect by creating virtual duplicate views with appropriate parallax adjustments
Solution Approach 2:
The patent replaces the mechanical optical system of multiple physical cameras with a computational system. A single camera captures the image, and then software-based image processing and mesh transformation algorithms generate the stereoscopic pair, substituting mechanical complexity with computational processing
2Reliability
If the distance between lenses in a stereo camera is increased to enhance the three-dimensional visual effect, then the intensity of the three-dimensional effect increases, but the camera case form factor becomes larger
Solution Approach 1:
The patent changes the parameter of interaxial distance from a fixed physical constraint to a flexible software parameter. By capturing images at different positions and using mesh-based transformation, the system can dynamically adjust the virtual lens separation distance to achieve desired three-dimensional effect intensity without physically increasing camera size
3Reliability
If multiple cameras are used to capture images from different positions, then the three-dimensional effect is achieved, but the complexity of targeting and simultaneously capturing images increases
Solution Approach 1:
The patent makes the system self-aligning through computational methods. Instead of requiring manual targeting and synchronization of multiple cameras, the system uses a single camera that captures images at different positions, then automatically computes the geometric relationships and applies appropriate transformations to generate the stereoscopic pair without requiring operator intervention for alignment
4Device complexity
If standard two-dimensional images are transformed into a stereo image pair using mesh-based transformation, then the cost and complexity are reduced, but the precision of preserving spatial relationships and features may be compromised
Solution Approach 1:
The patent segments the image into a mesh structure with multiple control points and cells. This segmentation allows independent transformation of different regions while preserving local geometric relationships, enabling high-precision feature preservation through localized mesh deformation rather than global image transformation
Data Source
AI summary
A set of features in a pair of images is associated to selected cells within a set of cells using a base mesh. Each image of the pair of images is divided using the base mesh to generate the set of cells. The set of features is defined in terms of the selected cells. A stereo image pair is generated by transforming the set of cells with a mesh-based transformation function. A transformation of the set of cells is computed by applying an energy minimization function to the set of cells. A selected transformed mesh and another transformed mesh are generated by applying the transformation of the set of cells to the base mesh. The mesh-based transformation function preserves selected properties of the set of features in the pair of images.