Facial Recognition False Positive Minimization via Location Data
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Solution Overview
Problem
In facial recognition applications, especially at public events, there is a challenge in accurately verifying the presence of individuals due to high rates of false positives, which can be exacerbated by the resource-intensive process of analyzing and parsing image data without associated contextual information.
Innovation Solution
An apparatus and method that utilize a combination of facial recognition data, such as two-dimensional and three-dimensional analytics, and convolutional neural nets, along with location data from user devices and image capture systems, to minimize false positives by associating images with user profiles based on proximity and contextual information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If facial recognition alone is used to identify people in pictures, then the process is simpler and faster, but false positives increase and accuracy decreases
Solution Approach 1:
The patent combines facial recognition analysis with location data verification to create a multi-factor identification system. The processor performs both facial recognition on images and compares location data from user devices with location characteristics extracted from images, merging these independent verification methods to reduce false positives while maintaining processing efficiency.
Solution Approach 2:
Location data serves as an intermediary verification layer between the image and the user profile. Instead of relying solely on facial recognition, the system uses location data from user devices as a mediator to confirm whether the detected person was actually present at the captured location, thereby reducing false positives.
2Reliability
If location data verification is added to facial recognition, then false positives decrease and accuracy improves, but resource consumption and processing complexity increase
Solution Approach 1:
The system performs preliminary location data collection and storage in user profiles before the actual verification process. Location characteristics of captured images are extracted and compared against pre-stored location data, allowing the system to quickly filter and verify without intensive real-time processing of all data elements.
Solution Approach 2:
The verification process focuses on local characteristics - specifically comparing location data from devices in the immediate vicinity with location characteristics extracted from the image. This localized approach to verification reduces the scope of processing required compared to a global analysis of all user data.
Data Source
AI summary
An apparatus can include a processor that can receive location data from a user device, and store the location data in a user profile data structure also storing facial recognition data. The processor can also receive at least one image, and can identify a location based at least in part on a set of characteristics within the at least one image. The processor can, for each user profile data structure stored in a database, compare location data in that user profile data structure to the location. The processor can, when the location data of the user profile data structure and the location match, conduct facial recognition to determine whether the user associated with the user profile data structure can be identified in the at least one image. The processor can then associate the at least one image with the user profile data structure if the user can be identified.