Smart Imaging Device Friend Prioritization in Crowds
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Solution Overview
Problem
It is challenging to visually recognize friends who are far away or in a large crowd, as existing methods lack efficient tools to aid in locating and prioritizing them based on social relationships and visibility factors.
Innovation Solution
A computer-implemented method and system for a smart imaging device that captures live image data, identifies friends using reference image data, generates a tracking record, and provides movement instructions to focus on selected individuals based on their social relationship strength and visibility, using a processor and movement sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual face detection and tagging is used in social media applications, then basic friend identification is achieved, but the system cannot efficiently prioritize or locate specific friends in large crowds or distant positions
Solution Approach 1:
The system segments the crowd detection task by first identifying all faces in the scene, then separately evaluating each detected face against reference images of friends. This two-stage approach (detection then identification) allows efficient processing of large crowds by breaking down the complex task into manageable segments, improving friend location efficiency without overwhelming system complexity
Solution Approach 2:
The system performs preliminary actions by pre-storing reference images of friends and their contact information before the actual crowd detection event. When a crowd scene is captured, the system can immediately compare against these pre-prepared references, eliminating the need for real-time manual identification and significantly improving detection efficiency
2Loss of information
If the imaging device captures all individuals in a crowd scene, then complete data is obtained, but the ability to quickly identify and focus on specific friends deteriorates
Solution Approach 1:
The system extracts only the relevant information (faces matching friend references) from the complete crowd scene data. After capturing all individuals, the system selectively identifies and extracts faces that match stored friend references, discarding irrelevant data. This extraction process maintains information completeness for analysis while enabling rapid friend identification by focusing only on matching faces
Solution Approach 2:
The system uses feedback mechanisms by comparing captured faces against stored friend references and providing immediate visual feedback through overlays and notifications. When a friend is detected, the system provides real-time feedback through on-screen indicators, allowing rapid identification without manual searching through all captured individuals
3Ease of operation
If the system prioritizes friends based on social relationship strength, then better friends are identified first, but the complexity of processing and ranking multiple factors increases
Solution Approach 1:
The system applies local quality by assigning different weights to different attributes (social relationship strength, visibility, distance) based on their local importance to the user's needs. Each attribute is evaluated and scored independently, then combined into an overall priority ranking. This allows the system to emphasize socially important friends while still considering physical detection factors, improving ease of operation through customizable priority scoring
Data Source
AI summary
A computer-implemented method for detecting and ranking individuals includes capturing live image data of a scene using an imaging device and identifying overlap between reference image data of the selected individuals and the live image data, wherein the overlap includes image data of the selected individuals in the scene. The method also includes capturing sets of image data of the selected individuals while the imaging device is in motion and recording the movement to provide a tracking record having instructions for positioning the imaging device where the imaging device captured the sets of image data of the selected individuals in the scene. The method further includes determining a score for each of the selected individuals in the scene based on a value related to an ability to view each friend and/or a social relationship value in order to enable a user to select who to aim the imaging device at.