Media Item Sharing via Time-Location Proximity for Subject Identification
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Solution Overview
Problem
Manually identifying and sharing media items that depict specific individuals is difficult and time-consuming.
Innovation Solution
A system and method for identifying media items based on proximity of capture locations and times to user locations using capture information and user information, facilitated by a processor executing machine-readable instructions, to automatically provide relevant media items to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual identification of media items depicting specific individuals is used, then accuracy of identification can be maintained, but time consumption and operational difficulty increase significantly
Solution Approach 1:
The patent replaces the manual mechanical process of identifying media items with an automated computational system. The processor executes machine-readable instructions to automatically compare capture information (location, time) with user information, substituting human manual review with algorithmic processing. This resolves the contradiction by eliminating time consumption and operational difficulty while maintaining identification accuracy through systematic automated comparison.
Solution Approach 2:
The system enables self-service identification where the media item identification process automatically serves itself without human intervention. The capture information and user information are automatically processed by the processor to identify and provide media items depicting users, making the system self-sufficient in performing the identification task that previously required manual human effort.
2Productivity
If automated identification based on proximity comparison is implemented, then productivity and ease of operation improve, but system complexity increases
Solution Approach 1:
The patent segments the identification system into distinct functional components: a capture information component to obtain media capture data, a user information component to obtain user location data, and an identification component to perform the comparison and selection. This segmentation allows the complex automated identification process to be broken down into manageable, specialized modules that can be independently developed and maintained, reducing the perceived system complexity while maintaining high productivity.
3Measurement precision
If comprehensive capture information and user information are collected and processed, then identification accuracy improves, but information processing requirements and system resources increase
Solution Approach 1:
The patent extracts only the essential comparison criteria (capture location and capture time) from the comprehensive capture information, and compares these specifically with user location and user time. Rather than processing all available information, the system extracts and processes only the relevant proximity-determining data points, thereby maintaining high identification accuracy while minimizing information processing requirements and system resource consumption.
Data Source
AI summary
Media items (e.g., images, videos) may be captured by one or more image capture devices. One or more of the media items may be identified as including/likely including depiction of a user based on proximity of capture of the media item(s) in time and location to the user. The identified media item(s) may be provided to the user.