Floorplan Feature Detection for Automated Spatial Indexing
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Solution Overview
Problem
Existing methods for manually annotating image locations in indoor environments are inefficient and time-consuming, especially in environments where GPS and indoor positioning systems are unreliable or unavailable, such as construction sites.
Innovation Solution
A spatial indexing system that uses a simultaneous localization and mapping (SLAM) algorithm to automatically determine the spatial locations of captured images, generating an immersive model and visualization interface without requiring manual annotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation of image locations is performed, then location accuracy can be ensured, but time consumption and labor efficiency deteriorate significantly
Solution Approach 1:
The patent replaces manual mechanical annotation with automated computer vision and deep learning algorithms. The system uses neural networks to automatically detect and recognize floorplan features in images, calculate camera positions through geometric algorithms, and generate spatial indexes without human intervention, thus eliminating time-consuming manual work while maintaining location accuracy.
Solution Approach 2:
The system enables self-service by allowing the image processing system to automatically determine its own spatial locations through feature detection and geometric calculation. The automated spatial indexing system processes images independently, extracting features and computing positions without requiring external manual annotation, achieving both efficiency and accuracy.
2Productivity
If automated spatial indexing is implemented, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex spatial indexing task into distinct modular components: feature detection module, floorplan recognition module, camera position calculation module, and spatial index generation module. Each module handles a specific subtask, making the overall complex system manageable and maintainable while achieving high processing efficiency through specialized optimization of each segment.
3Measurement precision
If multiple images are captured to monitor construction progress, then monitoring accuracy is improved, but the time required for capturing and indexing images increases
Solution Approach 1:
The patent implements continuous automated processing of multiple construction site images. The system continuously captures images at different time points and automatically processes them through the spatial indexing pipeline without interruption, maintaining continuous monitoring capability while eliminating the time delays associated with manual annotation of each image batch.
Data Source
AI summary
A spatial indexing system receives a sequence of images depicting an environment, such as a floor of a construction site, and performs a spatial indexing process to automatically identify the spatial locations at which each of the images were captured. The spatial indexing system also generates an immersive model of the environment and provides a visualization interface that allows a user to view each of the images at its corresponding location within the model.