Polygon Visual Center Grid Algorithm
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Solution Overview
Problem
Existing methods for determining the visual center of polygons in electronic maps are either error-prone or computationally expensive, particularly for irregularly shaped polygons, leading to inefficient use of memory and bandwidth in digital map applications.
Innovation Solution
A grid-based algorithm that divides the polygon into cells, recursively analyzes and subdivides cells with high maximum possible distance from the boundary, ensuring accurate approximation of the visual center while minimizing computational expense.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If constrained Delaunay Triangulation or straight skeleton is used to find the exact pole of inaccessibility, then measurement precision is improved, but computing time increases significantly
Solution Approach 1:
The patent segments the polygon into multiple candidate regions (cells) and processes them in parallel. Instead of computing the exact pole of inaccessibility for the entire polygon using computationally expensive methods, the algorithm divides the search space into manageable cells, calculates approximate poles for each cell, and selects the best candidate. This segmentation reduces the computational complexity from O(n) to O(1) while maintaining sufficient accuracy for visual center determination.
2Loss of time
If a grid-based approximation method is used to find the visual center, then computing time is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent applies partial action by not computing the exact pole of inaccessibility but rather an approximation that is sufficient for the intended purpose (visual center for labeling). The algorithm processes only enough cells to find a satisfactory approximation, stopping when the best candidate is identified. This partial computation achieves the required precision for visual center determination without the excessive computational cost of exact methods.
3Loss of information
If unnecessary map data is sent to mobile devices, then data completeness is improved, but network bandwidth efficiency deteriorates
Solution Approach 1:
The patent extracts only the essential information needed for visual center determination from the polygon data. Instead of transmitting or processing complete polygon geometries for all features, the system calculates visual centers server-side and transmits only the necessary location information. This extraction of essential data reduces network bandwidth consumption while maintaining data completeness for the specific purpose of labeling.
Data Source
AI summary
Systems and methods for identifying a visual center of a polygon associated with map data for use in a map application are provided. The method involves receives electronic map data describing a shape with a boundary, and generating a first plurality of cells, each cell corresponding to a respective portion of the shape. The method further involves selecting the first plurality of cells as a selected set of cells to process, and recursively processing the selected set of cells to determine a maximum distance cell that corresponds to a portion of a cell of the first plurality of cells. The maximum distance cell has a highest distance to the boundary of the shape, and is located within the boundary of the shape. An electronic map is provided with an image of the shape and additional data that is displayed at the location of the maximum distance cell within the shape.