Rooftop Reconstruction for Digital Map Tile Borders
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Solution Overview
Problem
Conventional digital map rendering systems face computational bottlenecks and inaccuracies when rendering buildings across map tile borders, leading to increased processing load and unrepresentative graphical elements due to incomplete elevation data and lack of association between vertices on different tiles.
Innovation Solution
A client device receives map tiles and terrain data, identifies edges intersecting tile borders, determines sample points, and calculates vertex elevation values to render buildings with a consistent top surface, reducing computational load and improving visualization accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional techniques calculate elevation values for each point on building footprint using multiple map tiles, then manufacturing precision of building representation is improved, but device complexity and processing time increase significantly
Solution Approach 1:
The system performs preliminary actions by identifying which map tiles contain vertices of the building footprint before performing elevation calculations. This allows the system to pre-determine the scope of data that needs to be processed and retrieved, avoiding unnecessary computations on tiles that don't contribute to the building representation.
Solution Approach 2:
The building footprint is segmented across multiple map tiles, and the system processes each tile independently by identifying vertices and edges specific to each tile. This segmentation allows parallel processing and reduces the computational burden on any single processing unit while maintaining overall accuracy.
2Manufacturing precision
If the system waits for all map tiles to be loaded before rendering, then manufacturing precision of building representation is improved, but loss of time increases significantly
Solution Approach 1:
The system performs preliminary identification of vertices and edges on map tiles that intersect with the building footprint before the complete set of tiles is available. This preliminary action allows rendering to begin with available data while continuing to process additional tiles in the background, reducing overall rendering time without sacrificing final accuracy.
Solution Approach 2:
The rendering process is made dynamic by allowing it to adapt as map tiles become available. The system can update building representations incrementally as new tiles are loaded, transitioning from an static wait-all-tiles approach to a dynamic progressive rendering approach that improves responsiveness.
3Manufacturing precision
If the system processes expansive sets of buildings within viewport at high zoom levels, then manufacturing precision is improved, but productivity decreases due to computational bottleneck
Solution Approach 1:
The viewport is segmented into multiple map tiles, and building processing is segmented by tile boundaries. This segmentation allows independent parallel processing of different tile regions, increasing overall rendering throughput while maintaining precision for each building within its respective tiles through the vertex identification method.
Solution Approach 2:
The system performs partial processing by initially focusing on identifying vertices and edges within available map tiles rather than attempting to process complete building footprints that may span multiple tiles. This partial action on available data enables faster initial rendering that can be refined as additional tiles are processed.
4Device complexity
If conventional techniques render buildings across map tile borders independently, then device complexity is reduced, but manufacturing precision deteriorates due to lack of association between vertices on different tiles
Solution Approach 1:
The system uses feedback by comparing geometric features (edges and vertices) of buildings across map tile borders to identify associations between partial building representations. This feedback mechanism allows the system to detect when vertices on different tiles belong to the same building and to merge or coordinate their rendering accordingly, improving accuracy without significantly increasing complexity.
Data Source
AI summary
A client device receives a first map tile, a second map tile, and map terrain data from a mapping system, the first and second map tiles together including map feature having a geometric base with a height value, the geometric base represented by a set of vertices split across the first and second map tiles. The client device identifies edges of the geometric base that intersect a tile border between the first and second map tiles. The client device determines a set of sample points based on the identified edges and determines a particular sample elevation value corresponding to a sample point in the set. The client device renders the map feature based on the particular sample elevation value and displays the rendering of the map feature.