Client-Side 3D Infrastructure Reconstruction via Metadata Streaming
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Solution Overview
Problem
Current methods for rendering three-dimensional infrastructure on client computers face challenges such as excessive memory requirements, high bandwidth demands, and limited scalability due to the need for large databases of geometric data, which hinder real-time rendering and streaming of complex scenes in simulators or games.
Innovation Solution
A technique that generates three-dimensional urban infrastructure geometric data on a client computer in real-time using pre-processed geographical and morphological data sets, allowing for the reconstruction of scenes with minimal memory requirements by streaming metadata and scripts from a server, enabling the generation of complex data with low bandwidth requirements and scalable geometry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If large databases of geometric data are generated to represent three-dimensional infrastructure, then the rendering quality and detail of the scene is improved, but the memory space requirements and processing time increase excessively
Solution Approach 1:
The patent segments the geometric data into two parts: metadata stored on the server and geometry data generated locally. The metadata includes information about building types, materials, and stylistic attributes, while the actual geometric representations are generated on-demand rather than stored in full. This segmentation allows high rendering quality without requiring large amounts of memory space to store complete geometric databases.
Solution Approach 2:
Instead of storing complete three-dimensional geometric models, the patent uses metadata that describes how to generate the geometry. The server provides copying instructions (metadata) rather than the actual geometric copies, allowing the client to reconstruct the geometry locally when needed. This reduces memory requirements while maintaining the ability to render detailed scenes.
2Adaptability or versatility
If holistic global data sets of geometric data are saved to enable real-time rendering, then the scene reconstruction capability is improved, but the bandwidth requirements and processing time become excessive
Solution Approach 1:
The patent extracts only the essential information (metadata) from the complete geometric data and transmits this minimized representation to the client. The metadata includes building types, materials, and stylistic attributes but excludes the bulk geometric data. This extraction allows the client to reconstruct scenes with high adaptability while minimizing bandwidth consumption during data transmission.
Solution Approach 2:
The server pre-processes and stores geometric data in an optimized format that can be quickly generated on-demand. The geometry generation algorithms and asset libraries are prepared in advance, allowing the client to reconstruct scenes rapidly when needed without requiring large amounts of data to be transmitted in real-time.
3Manufacturing precision
If complete three-dimensional geometric data is streamed to the client computer, then the rendering detail is improved, but the real-time performance and execution speed are reduced
Solution Approach 1:
The patent implements a dynamic geometry generation system where the client computer generates geometric data in real-time based on metadata and current rendering requirements. Rather than loading complete geometric databases, the system dynamically creates geometry on-demand, adjusting the level of detail based on rendering needs. This dynamic approach maintains high rendering detail while preserving real-time performance.
Solution Approach 2:
The system changes the parameters of data transmission and processing by working with metadata rather than complete geometric data. The metadata includes parameters such as building types, materials, and stylistic attributes, which are sufficient to generate the required geometry. This parameter change allows the system to maintain rendering detail while significantly improving real-time performance by reducing the amount of data that needs to be processed.
Data Source
AI summary
Two-dimensional aerial images and other geo-spatial information are processed to produce land classification data, vector data and attribute data for buildings found within the images. This data is stored upon a server computer within shape files, and also stored are source code scripts describing how to reconstruct a type of building along with compiled versions of the scripts. A software game or simulator executes upon a client computer in which an avatar moves within a landscape. A classifier classifies a type of building in the shape file to execute the appropriate script. Depending upon its location, a scene composer downloads a shape file and a compiled script is executed in order to reconstruct any number of buildings in the vicinity of the avatar. The script produces a three-dimensional textured mesh which is then rendered upon a screen of the client computer to display a two-dimensional representation of the building.