Anonymous Driver Matching With Irreversible Facial Feature Vectors
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Solution Overview
Problem
Existing shared vehicle management systems fail to protect driver privacy by storing facial images or IDs, violating privacy laws and requiring significant storage and management costs, while also risking exposure of passenger privacy.
Innovation Solution
A system that irreversibly encodes driver images into facial feature vectors, managing driving information anonymously by matching these vectors with driving records, ensuring privacy and reducing storage and management costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If driver facial images or IDs are stored for identification, then driver identification accuracy is improved, but driver privacy protection deteriorates
Solution Approach 1:
The patent extracts only the essential facial feature information from driver images and stores only this extracted feature data rather than the complete images or IDs. This allows identification functionality to be maintained while removing the harmful complete image storage that compromises privacy.
Solution Approach 2:
The patent creates a simplified copy of facial information in the form of feature vectors or hashes, which preserves the identification capability without containing the original sensitive image data. This copy can be stored and compared without exposing the actual driver images.
2Measurement precision
If driver facial images are stored for recognition, then driver identification capability is improved, but storage space requirements increase
Solution Approach 1:
The patent extracts only the essential facial feature information from driver images and stores only this extracted feature data rather than the complete images or IDs. This allows identification functionality to be maintained while removing the harmful complete image storage that compromises privacy.
Solution Approach 2:
The patent transforms the storage format from high-volume image data to compact parameter representations such as feature vectors or hashed values. This parameter transformation dramatically reduces the storage space required while maintaining the ability to perform driver identification.
3Measurement precision
If complete driver images are stored for analysis, then driving pattern analysis accuracy is improved, but management costs increase
Solution Approach 1:
The patent extracts only the essential facial feature information from driver images and stores only this extracted feature data rather than the complete images or IDs. This allows identification functionality to be maintained while removing the harmful complete image storage that compromises privacy.
Solution Approach 2:
The patent creates a simplified copy of facial information in the form of feature vectors or hashes, which preserves the identification capability without containing the original sensitive image data. This copy can be stored and compared without exposing the actual driver images.
Data Source
AI summary
A driver anonymity-ensured shared vehicle-driving information management system includes a main camera, a sensor, an auxiliary camera, a memory unit, and a processor. The processor includes a driving record generation section configured to generate a driving record of the vehicle on the basis of an image taken by the main camera and sensing data detected by the sensor, a facial feature vector extraction section configured to extract a driver facial feature vector by irreversibly encoding the driver image taken by the auxiliary camera so that the driver image is not able to be restored to the original driver image, and an anonymous driver driving information storage section configured to match the driver facial feature vector with the driving record and stores the matched data in the memory unit.