Map Data Anomaly Correction via Polygon Scaling
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Solution Overview
Problem
Conventional approaches to resolving map data inconsistencies and anomalies, such as elevation differences and polygon misalignments, are inefficient and often result in aesthetically poor representations of terrain and coastlines, especially when combining data from different vendors, leading to increased storage and processing requirements and user dissatisfaction.
Innovation Solution
A computer-implemented method that simplifies terrain meshes by removing collinear points, performs Delaunay triangulation, identifies and adjusts elevation anomalies, and uses medial axes to align polygons, ensuring accurate and visually pleasing map representations by distributing gaps and overlaps between adjacent polygons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If map data from different vendors is combined without adjustment, then data coverage is improved, but mismatches and errors appear in the rendered map
Solution Approach 1:
The patent applies local quality by making different parts of the map data have different properties. Specifically, it identifies regions with vendor mismatches and applies targeted adjustments (shifting, scaling, or blending) only to those specific polygon regions, while leaving other regions unchanged. This allows the system to maintain high precision in problematic areas while preserving the overall data coverage from multiple vendors.
Solution Approach 2:
The patent employs parameter changes by modifying the geometric parameters of polygons from different vendors. It changes location parameters (shifting polygons by calculated offsets), scale parameters (adjusting polygon sizes), and blending parameters (interpolating between vendor data) to resolve mismatches. These parameter adjustments enable accurate rendering while maintaining comprehensive data coverage.
2Measurement precision
If terrain meshes are highly detailed, then elevation accuracy is improved, but storage and processing requirements increase
Solution Approach 1:
The patent applies partial action by selectively simplifying only those portions of terrain meshes that are less critical to overall accuracy. It identifies and removes redundant triangles and collinear points from less prominent terrain features, while preserving detailed elevation data in critical areas. This selective approach reduces storage requirements while maintaining necessary elevation accuracy for important geographic features.
3Productivity
If collinear points are removed from terrain meshes, then triangle count is reduced, but processing speed may be affected
Solution Approach 1:
The patent uses parameter changes by modifying the spatial distribution of points in terrain meshes. It removes collinear points and simplifies triangle configurations, thereby changing the geometric parameters of the mesh representation. This reduces the total number of triangles and improves processing efficiency while maintaining the essential terrain features through intelligent point selection and preservation of critical geometric relationships.
Data Source
AI summary
Techniques described herein are used to identify buildings that intersect or otherwise overlap a road, and independently scaling the buildings until they no longer overlap. For example, a computer system may identify an intersection condition corresponding to an intersection between a first polygon of a first type and a second polygon of a second type. The first polygon may include a set of edges connected by a set of vertexes. The computer system may select a first pivot point for the first polygon, which includes a vertex of the set of vertexes or a midpoint of one edge of the set of edges. The computer system may perform an iterative scaling operation. The computer system may determine, based on the iterative scaling operation, a polygon transformation that avoids the intersection condition. The computer system may cause rendering, on a display, of a map view that includes the polygon transformation.