Map Rendering System for Automatic Neighborhood Highlighting
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Solution Overview
Problem
Existing digital map systems prioritize navigation features over points of interest, making it difficult for casual visitors to explore areas without a specific destination in mind.
Innovation Solution
A computer-implemented method that retrieves metadata for map features, categorizes them based on common keywords, determines areas of high density, and assigns modified styles to highlight areas of interest, allowing for enhanced visualization of points of interest and neighborhoods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If map features are prioritized based on navigation importance, then navigation efficiency is improved, but visibility of points of interest and neighborhoods deteriorates
Solution Approach 1:
The patent applies local quality by differentiating the display treatment of map features based on their category and density. Areas with high density of points of interest receive enhanced visual treatment (highlighting, coloring, labeling) while navigation-critical features maintain their traditional prominence. This allows different regions of the map to have different visual priorities, simultaneously supporting both navigation efficiency and points of interest discovery.
Solution Approach 2:
The patent utilizes color changes to visually distinguish areas with high density of points of interest from other map regions. By applying color overlays, shading, or highlighting to specific geographic areas, the system makes points of interest and neighborhoods visually prominent without obscuring the underlying navigation infrastructure. This resolves the contradiction by making POI visibility enhanced through color while preserving navigation feature visibility.
2Adaptability or versatility
If map data is processed to highlight areas of interest, then user exploration capability is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the map data processing into distinct categorical groups (restaurants, entertainment, shopping, etc.) and processes each category separately. By dividing the overall processing task into smaller categorical segments, the system can apply density analysis and visual highlighting to specific categories without overwhelming computational complexity. This segmentation enables enhanced user exploration capability while managing data processing complexity through modular category-based handling.
Solution Approach 2:
The patent changes the parameter of visual prominence dynamically based on calculated density thresholds. Instead of processing all map features uniformly, the system adjusts display parameters (color, label visibility, highlighting intensity) only for areas exceeding specific density thresholds. This parameter-based filtering reduces processing complexity by focusing computational resources on significant areas while maintaining user exploration capability through targeted visual enhancements.
Data Source
AI summary
A graphics or image rendering system, such as a map image rendering system, may mark areas of interest on a map based on metadata associated with one or more features of the map. Additional map features may be created to mark the areas of interest or styles of existing map features may be modified to mark the areas of interest.