Automated Sensitive Building Recognition in HD Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The efficiency of manual recognition methods for desensitizing sensitive building information in high definition map construction is low, requiring significant time and labor when dealing with large amounts of original image information.
Innovation Solution
An image recognition method that uses desensitized map data and positioning information to automatically identify sensitive buildings, reducing the need for manual recognition by determining target object information through communication with a map data server or local map data, and allowing for efficient deletion of sensitive building information from images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual recognition method is used to identify sensitive buildings, then recognition accuracy can be maintained, but recognition efficiency deteriorates and labor costs increase
Solution Approach 1:
The patent segments the sensitive building identification process into multiple components: obtaining to-be-recognized images with building information and positioning data, querying desensitized map data based on positioning information, comparing building information against desensitized data, and automatically identifying sensitive buildings. This segmentation enables automated processing while maintaining accuracy standards.
Solution Approach 2:
The patent introduces desensitized map data as an intermediary element between the to-be-recognized images and the identification result. This intermediary contains pre-processed sensitive building information that facilitates automated comparison and identification, reducing the need for manual recognition while maintaining accuracy.
2Reliability
If manual recognition method is used to desensitize original image information, then desensitization quality can be ensured, but time consumption increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-processing sensitive building information into desensitized map data before the actual recognition process. This pre-processed data contains organized sensitive building information that can be quickly queried and compared, ensuring desensitization quality while significantly reducing processing time during the actual image recognition phase.
Solution Approach 2:
The patent uses desensitized map data as a copy or representation of sensitive building information that can be efficiently queried and compared against to-be-recognized images. This copying approach allows automated systems to access sensitive building data without manually processing original images, thereby maintaining desensitization quality while reducing time consumption.
3Productivity
If automated recognition method is used, then recognition efficiency improves, but system complexity increases
Solution Approach 1:
The patent applies universality by designing the automated recognition system to handle multiple types of building information and positioning data through a unified process. The system can process various image formats, positioning information types, and desensitized map data structures using the same core methodology, which manages complexity while maintaining high recognition efficiency.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system queries desensitized map data based on positioning information from to-be-recognized images, compares results, and automatically identifies sensitive buildings. This feedback loop enables automated decision-making that improves efficiency while the structured feedback process helps manage system complexity through clear decision pathways.
Data Source
AI summary
In an image recognition method, a terminal determines, based on first positioning information, target object information corresponding to building information in a to-be-recognized image in desensitized map data. The desensitized map data does not include a sensitive building. Then, when the terminal determines that the target object information does not include the building information, the terminal determines that the map data does not include the building information. In this case, the terminal determines to recognize the building information as a sensitive building. In other words, the terminal may recognize, by using the desensitized map data, building information corresponding to a sensitive building in the to-be-recognized image.