Dynamic 2D to 3D Map Projection via Distance-Adaptive Transformation
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Solution Overview
Problem
Current map rendering systems fail to effectively integrate two-dimensional (2D) map data with three-dimensional (3D) scenes, lacking elevation information and vertical relationships, which limits the immersive experience and accuracy of map elements like roads and terrain in digital maps.
Innovation Solution
A method and system that transform 2D map data from a 2D coordinate system to a 3D coordinate system using linear or non-linear transformations based on the distance between the virtual camera and the 3D geometry, accounting for the Earth's curvature, to accurately render and overlay 2D map elements on 3D geometry, using a software module that can execute on CPUs or GPUs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-linear transformation is used to account for Earth's curvature, then accuracy is improved, but computational complexity increases
Solution Approach 1:
The system dynamically selects between linear and non-linear transformation methods based on the distance between the virtual camera and the 3D geometry. When the camera is close to the geometry, linear transformation is used for efficiency. When the camera is far away, non-linear transformation is applied to account for Earth's curvature and maintain accuracy. This dynamic adaptation resolves the contradiction by adjusting computational complexity based on actual viewing conditions.
Solution Approach 2:
The system changes the transformation parameter (linear vs. non-linear) based on the camera-geometry distance threshold. This parameter change allows the system to switch between computational modes, using the simpler linear transformation when acceptable and the more accurate non-linear transformation when necessary, thus balancing accuracy and complexity.
2Productivity
If linear transformation is used for close camera distances, then computational efficiency is improved, but accuracy deteriorates for larger distances
Solution Approach 1:
The system dynamically adjusts the transformation method based on camera distance. For close distances where linear transformation maintains sufficient accuracy, it uses the efficient linear method. For far distances where curvature effects become significant, it switches to the more accurate non-linear method. This dynamic selection optimizes both efficiency and accuracy based on actual viewing conditions.
3Loss of information
If 2D map data is integrated with 3D scenes, then information completeness is improved, but integration complexity increases
Solution Approach 1:
The system uses mathematical transformation (matrix operations) to replace complex geometric integration processes. By representing both 2D map data and 3D scene data in coordinate systems that can be transformed into each other through defined mathematical operations, the system simplifies the integration process while maintaining information completeness.
Solution Approach 2:
The system transforms data between different coordinate system representations (2D geographic coordinates to 3D Cartesian coordinates) based on viewing conditions. This parameter transformation allows seamless integration of 2D and 3D data without requiring complex unified modeling, resolving the integration complexity while preserving elevation information.
Data Source
AI summary
A map element parameterized in a two-dimensional (2D) coordinate system is applied to to three-dimensional (3D) geometry, parameterized in a 3D coordinate system, of a geographic area with which the map element is associated. The 3D geometry is rendered according to the selected perspective of a virtual camera. An approximate distance between the virtual camera and the 3D geometry is compared to a threshold value. A position of the map element is determined relative to the 3D geometry using (i) a linear transformation between the 2D coordinate system and the 3D coordinate when the approximate distance is smaller than the threshold value, and (ii) a non-linear transformation between the 2D coordinate system and the 3D coordinate system when the approximate distance is larger than the threshold value.