Geometric Correction of Rough 3D Wireframe Models from Photographs
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Solution Overview
Problem
Current methods for generating three-dimensional computer models of roofs from two-dimensional photographs are either fast but inaccurate, require prior knowledge of roof facet pitches, or are complex and time-consuming, and often incompatible with widely used CAD software.
Innovation Solution
The development of a method involving wireframe rectification, metadata derivation, in-plane normalization, extrusion into a rough 3D wireframe, and correction of 3D wireframes, which can be used independently or in combination to produce accurate and geometrically correct 2D and 3D models that can be easily converted for import into third-party CAD software without requiring prior knowledge of roof facet pitches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tracing method is used to generate wireframe model from photograph, then generation speed is fast and compatibility with CAD tools is good, but manufacturing precision deteriorates due to incorrect line lengths and poor pitch determination
Solution Approach 1:
The patent transitions from 2D photograph tracing to 3D wireframe modeling by introducing height information. The system automatically determines roof facet pitches and generates three-dimensional models with accurate line lengths by computing Z-coordinates based on determined pitches, thereby resolving the precision issues inherent in 2D tracing methods.
Solution Approach 2:
The patent replaces manual tracing operations with automated computer vision and image processing algorithms. The system automatically detects roof features, determines pitches through image analysis, and generates wireframe models without manual intervention, eliminating the precision errors associated with manual tracing while maintaining fast generation speeds.
2Ease of operation
If tracing method is used to generate wireframe model, then generation process is simple, but measurement precision deteriorates due to poor ability to determine pitches
Solution Approach 1:
The system performs self-service by automatically determining roof facet pitches through image analysis without requiring user input or prior knowledge. The algorithm independently analyzes the photograph, identifies roof features, computes pitch angles, and generates the complete wireframe model, thereby maintaining operational simplicity while achieving high measurement precision.
Solution Approach 2:
The patent introduces an intermediary computational layer that bridges the gap between simple photograph input and accurate pitch measurement. The system uses image processing algorithms as intermediaries to extract geometric information, calculate pitches, and generate precise wireframe models, thereby achieving high measurement precision without complicating the user interface.
3Manufacturing precision
If primitive alignment method is used to create geometrically correct models, then manufacturing precision is improved, but device complexity increases due to complex user interface software
Solution Approach 1:
The patent replaces complex interactive primitive alignment operations with automated image processing and geometric computation. The system automatically analyzes the photograph, determines roof pitches, and generates geometrically correct wireframe models through algorithmic processing, thereby achieving high manufacturing precision while eliminating the need for complex user interface software.
Solution Approach 2:
The system performs self-service by automatically generating geometrically correct models without requiring user interaction for primitive selection, alignment, or adjustment. The computational algorithms independently complete the entire modeling process, thereby achieving high geometric correctness while maintaining simple software interfaces.
4Measurement precision
If multiple photographs from different angles are used to create 3D model, then measurement precision is improved by deriving pitches from photograph content, but loss of time increases due to detailed 3D modeling requirements
Solution Approach 1:
The patent applies partial action by using a single overhead photograph instead of multiple photographs from different angles. The system extracts sufficient pitch information from the single image through specialized image processing, thereby achieving accurate pitch derivation while significantly reducing the time required for data collection and processing compared to multi-photograph methods.
Solution Approach 2:
The system performs preliminary action by pre-processing the single photograph to extract all necessary geometric information before wireframe generation. The image processing algorithms pre-calculate pitch angles and roof features from the photograph, enabling rapid wireframe model creation without requiring time-consuming multi-angle photography and complex 3D reconstruction.
5Adaptability or versatility
If third party CAD software compatibility is required, then adaptability is improved, but manufacturing precision deteriorates due to inability to easily import detailed 3D models
Solution Approach 1:
The patent segments the wireframe model into standardized geometric elements that can be easily imported into third-party CAD software. The system generates wireframe models with well-defined vertices, edges, and faces that conform to common CAD data structures, thereby improving adaptability while maintaining manufacturing precision through structured data output.
Solution Approach 2:
The system creates universally compatible wireframe models that can be imported into multiple third-party CAD software packages. By using standard geometric representations and common data formats, the patent achieves broad software compatibility while preserving the geometric precision of the generated models, allowing seamless integration with various construction and design tools.
Data Source
AI summary
Geometric correction of rough wireframe models derived from photographs may include rectification of either a 2D or 3D original wireframe model of a roof structure, derivation of metadata from the original wireframe, in-plane normalization of the wireframe, extrusion into a “rough” 3D wireframe based on the normalized wireframe, and correction of the “rough” 3D wireframe. The correction and normalization may be an iterative process based on initial pitch values, metadata derived from the original or corrected wireframe models and defined constraints regarding relationships between roof portions or segments. The iterative process may repeat adjusting the wireframe model until the adjusting converges to a stable state according to the various defined constraints.