Roof Analysis Tool for Accurate 3D Map Rendering
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Solution Overview
Problem
Mobile devices face challenges in providing responsive mapping experiences due to high computational complexity, bandwidth demands, and storage requirements when constructing accurate three-dimensional models of map regions, particularly in rendering building roofs, which are not adequately addressed by traditional raster data or simple extrusions of building footprints.
Innovation Solution
A roof analysis tool that operates on both mobile devices and servers to generate parameter sets describing roof types and shapes, using three-dimensional mesh data and footprint information to create compact representations of roof planes, allowing for accurate and efficient rendering of building roofs in a three-dimensional map view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high definition mapping data is processed on mobile devices to construct accurate roof representations, then the accuracy of three-dimensional model is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The system segments the roof representation task into two parts: (1) extracting roof plane parameters from 3D mesh data on the server, and (2) rendering the simplified roof representations on the mobile device. This segmentation allows the computationally intensive 3D modeling to be performed remotely while the mobile device only handles the simplified rendering, thus maintaining accuracy without excessive computational complexity on the device.
Solution Approach 2:
Instead of copying the entire high-definition 3D mesh data to the mobile device, the system creates a simplified copy that retains only the essential roof plane parameters (position, orientation, size). This selective copying approach preserves the necessary information for accurate roof representation while dramatically reducing the data size and processing requirements on the mobile device.
2Measurement precision
If three-dimensional mesh data is processed on mobile devices to generate accurate roof models, then the realism of map view is improved, but storage requirements and bandwidth demands increase
Solution Approach 1:
The system extracts only the critical parameters needed for roof representation from the full 3D mesh data. Specifically, it extracts plane equations and geometric characteristics that define the roof structure, while discarding redundant texture and detail information. This extraction process maintains the essential realism of the roof representation while significantly reducing the quantity of data that needs to be stored and transmitted to the mobile device.
Solution Approach 2:
The system transforms the detailed 3D mesh data into a parameterized representation using simplified geometric parameters (plane normals, intercepts, vertex coordinates). This parameter change reduces the data from complex triangular mesh formats to compact parameter sets that convey the same visual information with much lower storage requirements and bandwidth consumption.
3Measurement precision
If detailed texture information is extracted and stored on mobile devices, then the visual accuracy of building roofs is improved, but storage capacity requirements increase
Solution Approach 1:
The system extracts only the geometric parameters of roof planes from the 3D mesh data, completely omitting texture information. The visual accuracy is maintained through the use of simplified geometric representations and basic material properties rather than detailed textures. This extraction approach preserves the essential visual characteristics of roofs while eliminating the need to store large texture files on the mobile device.
Data Source
AI summary
Methods and apparatus for a roof analysis tool for constructing a parameter set, where the parameter set is derived from mapping data for a map region, and where the parameter set describes the roofs for the buildings within the map region. In some cases, the parameter set includes a list of roof type identification values and the respective buildings in the map region for which a given roof type identification value corresponds. The roof analysis tool may operate on a server and work in conjunction with a mobile device, where the mobile device may display map views of a map region such that the map view is based on a three-dimensional model of the map region, and where a portion of the three-dimensional model is based on data generated on the mobile device and a portion of the three-dimensional model is based on data generated on the server.