Floorplan Feature Matching for GPS-Free Image Spatial Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manually annotating image locations in indoor environments, such as construction sites, is inefficient and time-consuming, especially when relying on GPS or RF signals that are unreliable or absent.
Innovation Solution
A spatial indexing system uses a SLAM algorithm to automatically determine the spatial locations of captured images, generating an immersive model and visualization interface without manual annotation, allowing users to view images at their corresponding locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual annotation is used to tag image locations, then location accuracy can be ensured, but the process becomes inefficient and time-consuming
Solution Approach 1:
The system performs self-service by automatically determining spatial locations through SLAM algorithms and floorplan feature matching, eliminating the need for manual annotation. The image capture system autonomously processes images to generate spatial indexes and immersive models without human intervention in the tagging process.
Solution Approach 2:
The patent replaces the mechanical manual annotation process with an automated computational system. SLAM algorithms and computer vision techniques substitute human operators, using image processing and algorithmic computation to automatically determine locations and generate spatial indexes.
2Extent of automation
If GPS or RF signals are used for location tagging, then automated location determination is achieved, but reliability deteriorates in indoor environments
Solution Approach 1:
The patent introduces floorplan features as an intermediary between the image capture system and location determination. Instead of relying directly on unreliable GPS or RF signals, the system uses visual features extracted from floorplans (walls, doors, windows) as intermediate reference points to accurately determine spatial locations in indoor environments.
Solution Approach 2:
The system creates a virtual copy or representation of the physical environment through floorplan images and spatial indexes. This digital replica allows the system to determine locations by matching captured images against the copied floorplan features, bypassing the need for unreliable external signals.
3Ease of operation
If automated spatial indexing is implemented, then user input is reduced, but system complexity increases
Solution Approach 1:
The spatial indexing system performs multiple functions within a single integrated framework: it captures images, extracts features, performs SLAM processing, matches floorplan features, determines locations, and generates immersive models. This multi-functionality consolidates complexity into a unified system that automatically handles the entire spatial indexing workflow.
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.