3D Interior Structure Modeling From Exterior Imagery
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Solution Overview
Problem
Existing methods for determining interior layouts of structures are slow and cumbersome, often impractical in emergency scenarios where architectural plans are unavailable, necessitating a rapid and automated process using exterior imagery to predict interior layouts.
Innovation Solution
Utilizing machine learning models to analyze exterior imagery, identify exterior surfaces and features, and generate three-dimensional representations of both exterior and interior structures, aligning interior features with exterior constraints and common construction practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to determine interior layouts, then accuracy may be maintained, but the process is slow and cumbersome
Solution Approach 1:
The patent replaces traditional manual or mechanical methods of interior layout determination with machine learning-based automated image analysis. The system uses trained neural networks to automatically process exterior imagery and predict interior layouts, eliminating the need for slow manual measurement and drafting processes while maintaining or improving accuracy.
Solution Approach 2:
The patent employs pre-trained machine learning models that have been previously trained on large datasets of architectural imagery. This preliminary training action enables the system to rapidly predict interior layouts from exterior images without requiring time-consuming on-site measurements or manual analysis during emergency scenarios.
2Reliability
If architectural plans are available, then interior layouts can be determined accurately, but plans are often unavailable in emergency scenarios
Solution Approach 1:
The patent inverts the traditional approach by predicting interior layouts from exterior imagery rather than extracting interiors from existing architectural plans. The machine learning model learns the relationship between exterior features and interior configurations, enabling accurate predictions even when no interior plans are available, thus providing adaptability to emergency scenarios.
Solution Approach 2:
The system creates accurate digital copies or predictions of interior layouts based solely on exterior imagery analysis. The machine learning model generates virtual representations of interior spaces that mirror what would be obtained from actual architectural plans, enabling users to work with copied interior data derived from exterior observations.
3Extent of automation
If manual methods are used to analyze exterior imagery, then detailed interior models can be created, but the process becomes complex and time-consuming
Solution Approach 1:
The patent replaces complex manual analysis processes with automated machine learning systems. Trained neural networks automatically perform feature extraction, pattern recognition, and interior layout prediction from exterior imagery, eliminating the need for manual measurement, documentation, and interpretation steps that would increase complexity and time requirements.
Data Source
AI summary
Methods and systems for improved prediction and generation of structure interiors are provided. In one embodiment a method is provided that includes receiving exterior imagery of the structure and determining an exterior surface of the structure with a machine learning model. The exterior surface may enclose exterior portions of the structure. The machine learning model may further determine exterior features of the structure and may determine, based on the exterior surface of the exterior features, an interior model of the structure. A three-dimensional representation of interior and exterior portions of structure may be generated based on the exterior surface and the interior model.