Automated Video Metadata Identification Using Temporal Position Analysis
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Solution Overview
Problem
Current metadata tagging processes for TV commercials rely heavily on human intervention and existing automated systems struggle to accurately identify primary metadata, such as product or brand information, from video frames, often misclassifying secondary metadata as primary.
Innovation Solution
A method and system that perform image analysis on video frames to identify product-related logos, text, and brand-related elements, using persistence, prominence, dominance, and temporal metrics to categorize their temporal position within the commercial, thereby accurately assigning primary metadata candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated image analysis is used to identify metadata candidates in video frames, then productivity is improved, but measurement precision deteriorates due to misclassification of secondary metadata as primary metadata
Solution Approach 1:
The patent segments the metadata identification process into distinct phases: initial automated detection of all potential metadata candidates, followed by a filtering stage that separates primary metadata from secondary metadata using multiple criteria (temporal position, persistence, prominence, dominance). This segmentation allows the system to maintain high productivity while improving precision through structured multi-stage processing.
Solution Approach 2:
The patent applies preliminary filtering actions by analyzing temporal position, persistence, prominence, and dominance characteristics before final metadata classification. These preliminary analyses prepare the data by identifying patterns and characteristics that will guide the subsequent classification decision, enabling more accurate differentiation between primary and secondary metadata.
2Measurement precision
If manual human review is used to verify metadata candidates, then measurement precision is improved, but productivity deteriorates due to time-consuming verification processes
Solution Approach 1:
The patent implements self-service by enabling the automated system to perform its own verification and filtering operations. The system uses algorithmic analysis of temporal position, persistence, prominence, and dominance to automatically differentiate primary from secondary metadata, replacing the need for manual human review while maintaining high accuracy. This self-service capability preserves productivity while achieving precision previously requiring human intervention.
3Measurement precision
If multiple analysis criteria (temporal position, persistence, prominence, dominance) are applied to filter metadata candidates, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex analysis into four distinct analytical dimensions (temporal position, persistence, prominence, dominance), each handling a specific aspect of metadata characterization. This segmentation makes the overall complex process more manageable and systematic, allowing the system to achieve high precision through multiple specialized analyses rather than one monolithic complex analysis.
Solution Approach 2:
The patent creates a universal filtering framework that applies multiple analysis criteria in an integrated manner. The same analytical infrastructure processes all four criteria (temporal position, persistence, prominence, dominance) to collectively determine metadata classification, making the system multi-functional while managing complexity through unified processing architecture.
Data Source
AI summary
A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, categorizing a temporal position of the identified video frames within the commercial as being in either a beginning or ending portion of the commercial, or a middle portion of the commercial, and assigning to the commercial the identified products or brands as primary metadata candidates when the temporal position of the identified video frames within the commercial is in either the beginning or ending portion of the commercial.