Geographic Location Point Spatial Relationship Extraction via Signboard Recognition
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Solution Overview
Problem
Current methods for determining geographic location point spatial relationships are either inaccurate due to coordinate errors or inefficient due to reliance on manual labeling, with existing automated methods suffering from significant errors and limited coverage.
Innovation Solution
A method and apparatus that utilize signboard recognition on real-scene images collected by terminal devices to determine geographic location point pairs and their spatial relationships using shooting parameters, such as positioning coordinates and angles, to calculate precise spatial relationships between geographic location points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If coordinate-based methods are used to determine spatial relationships, then automation is improved, but measurement precision deteriorates due to coordinate errors
Solution Approach 1:
The patent introduces signboard recognition as an intermediary element between automated coordinate-based methods and precise spatial relationships. By recognizing signboards in images and using their visual features as mediators, the system can determine spatial relationships with higher precision while maintaining automation. The signboard serves as a reference object that bridges the gap between automated processing and accurate measurement.
2Measurement precision
If manual labeling methods are used to determine spatial relationships, then measurement precision is improved, but productivity deteriorates due to inefficient manual processes
Solution Approach 1:
The system enables self-service by allowing terminal devices to automatically capture images, perform signboard recognition, and determine spatial relationships without requiring manual intervention. The automated image processing and recognition algorithms perform the work that would otherwise require manual labeling, thereby maintaining high precision while dramatically improving productivity.
Solution Approach 2:
The patent replaces the mechanical manual labeling process with an automated optical and computational system. Terminal devices capture images, computer vision algorithms recognize signboards and extract spatial information, and processing systems automatically determine relationships between geographic location points. This substitution eliminates manual labor while preserving measurement precision through sophisticated image analysis.
3Productivity
If existing automated methods are used, then productivity is improved, but measurement precision deteriorates due to significant errors
Solution Approach 1:
The patent transitions from two-dimensional coordinate data to three-dimensional spatial understanding by utilizing images as an additional dimension of information. By analyzing the visual appearance, position, and orientation of signboards in images along with their coordinates, the system creates a more robust spatial model that resolves ambiguities and errors present in coordinate-only approaches, thereby improving precision while maintaining automated processing efficiency.
Data Source
AI summary
The present application discloses a method and apparatus for extracting a geographic location point spatial relationship, and relates to the field of big data technologies. A specific implementation solution is as follows: determining geographic location point pairs included in real-scene images by performing signboard recognition on the real-scene images collected by terminal devices; acquiring at least two real-scene images collected by the same terminal device and including the same geographic location point pair; and determining a spatial relationship of the same geographic location point pair by using shooting parameters of the at least two real-scene images. The geographic location point spatial relationship extracted through the present application has higher accuracy and a coverage rate.