Facial Recognition Proximity Notification System
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Solution Overview
Problem
Existing facial recognition systems at events and venues face challenges in accurately analyzing images and videos, often requiring significant resources and failing to provide contextual data, which limits their ability to notify users of connected individuals present in the vicinity.
Innovation Solution
A system comprising a processor, memory, and communication interface that receives images from image capture devices, performs facial recognition, identifies connected users based on user profiles and connection databases, and sends notifications when a confidence level meets a criterion, indicating proximity to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If facial recognition technology is used to identify people in pictures and video streams at venues and events, then users can be notified when connected individuals are present, but the system requires significant computational resources and processing time
Solution Approach 1:
The system performs preliminary actions by pre-processing images to detect faces and pre-comparing detected faces against a database of connected individuals' facial data before generating notifications. This reduces the computational burden during real-time operation by preparing data structures and indexing facial features in advance, allowing faster matching when actual identification is needed.
2Loss of information
If comprehensive facial recognition analysis is performed on all images and video streams, then all connected individuals can be identified, but the system complexity and resource requirements increase significantly
Solution Approach 1:
The system extracts only the essential facial features and characteristics from images and video streams that are necessary for identification, rather than analyzing all visual data. By isolating and processing only the relevant facial data, the system maintains comprehensive identification capability while reducing overall system complexity and resource consumption.
3Loss of time
If real-time facial recognition notification is implemented, then users receive immediate alerts when connected individuals are nearby, but the processing speed and response time requirements increase
Solution Approach 1:
The system performs preliminary face detection and feature extraction as images and video frames are captured, preparing the data for rapid comparison against connected individuals' profiles. By pre-processing and indexing facial features before actual identification queries, the system enables real-time notifications without requiring excessive processing speed during the critical notification moment.
Data Source
AI summary
An apparatus includes processor in communication with a memory and a communication interface. The processor is configured to receive, via a network and the communication interface, at least one image and to analyze the at least one image via facial recognition to define an analyzed data set. The processor is configured to (1) identify a user based on data included in user profile data structure, (2) identify a set of people connected to the user based on user connection data from at least one connection database, (3) compare the analyzed data set to facial image data of a person connected to the user, and (4) define a confidence level based on the comparison. When the confidence level satisfies a criterion, the processor can send to a client device a signal indicative of a notification that the person is within a predetermined proximity of the user.