Digital Media Tag Association via Feature and Location Comparison
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Solution Overview
Problem
Manually labeling digital media objects with metadata tags is a time-consuming process, and existing methods lack efficiency in automatically associating similar media objects based on features, timestamps, and geographical coordinates.
Innovation Solution
A system and method that receive multiple media objects, compare them based on features such as depictions of people, timestamps, and geographical coordinates, and selectively associate metadata tags between media objects, allowing for automatic generation of digital media albums.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual labeling of digital media objects with metadata tags is performed, then accuracy of metadata association is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary automatic labeling by comparing features, timestamps, and geographical coordinates of media objects to generate candidate metadata associations before user review. This preliminary action handles the bulk of labeling automatically, reducing the time users need to spend on manual labeling while maintaining accuracy through subsequent user verification of the pre-generated associations.
2Productivity
If automatic comparison of media objects is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The comparison system is segmented into three independent modules: feature comparison (visual content), timestamp comparison (temporal information), and geographical coordinate comparison (location data). Each module operates independently and contributes to the overall similarity assessment. This segmentation reduces system complexity by breaking down the complex comparison task into manageable, specialized components that can be implemented and maintained separately.
3Measurement precision
If selective association of metadata tags is performed, then metadata precision is improved, but processing time increases
Solution Approach 1:
The system performs self-service by automatically generating candidate metadata associations through comparison of media object features, timestamps, and geographical coordinates. This automatic self-service handles the initial labeling task without user intervention, reducing processing time. The precision is maintained because the system only presents carefully selected candidate associations for user confirmation, rather than requiring users to create all associations from scratch or process every possible combination.
Data Source
AI summary
Digital media categorization can include receiving information including a plurality of media objects and a metadata tag descriptive of at least a first media object; comparing the first media object with a second media object; and selectively associating the first media object's metadata tag with the second media object based on a result of the comparison. Each media object can include a digital image.