Commercial Metadata Identification via Audio-Visual Cross-Validation
Solution Overview
Problem
Current metadata tagging processes for TV commercials rely heavily on human intervention and conventional image analytics, which are inadequate for accurately identifying primary metadata such as product or brand information, often misclassifying secondary metadata as primary.
Innovation Solution
A method and system that perform image analysis on video frames to identify product-related logos and text, combined with audio analysis to confirm brand associations, and assign primary metadata candidates based on persistence, prominence, dominance, and temporal metrics, ensuring accurate identification of primary metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image analytics are used to identify objects in video frames, then object detection capability is provided, but accuracy in identifying primary metadata is insufficient and secondary metadata is misclassified as primary
Solution Approach 1:
The patent combines image analysis results with audio analysis results to identify primary metadata. By merging multiple analysis modalities (visual and auditory) and cross-referencing them against a database of known commercials, the system achieves more reliable and accurate primary metadata identification than conventional image analytics alone could provide.
2Productivity
If automated processes are used for metadata identification, then productivity is improved, but accuracy of metadata identification deteriorates compared to manual processes
Solution Approach 1:
The system employs feedback mechanisms where image analysis and audio analysis results are cross-validated against each other and against database information. This feedback loop allows the automated process to correct its own errors and improve accuracy while maintaining high productivity, eliminating the need for manual spot-checking.
Solution Approach 2:
The patent creates a universal automated system that handles multiple metadata identification tasks simultaneously through multi-functional analysis (image analysis, audio analysis, database comparison). This single system performs what previously required multiple specialized processes including manual verification, achieving both high productivity and maintained accuracy.
3Reliability
If multiple analysis methods are combined to improve accuracy, then metadata identification reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the metadata identification process into distinct functional modules: image analysis module, audio analysis module, database comparison module, and integration module. This segmentation allows each component to be optimized independently while working together to achieve high reliability, managing complexity through modular design rather than monolithic 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, performing audio analysis on the commercial to identify audio associated with one or more identifiable products or brands in the commercial, comparing the products and brands identified by the image analysis with the products and brands identified by the audio analysis, and identifying similar products and brands; and assigning to the commercial a product or brand as a primary metadata candidate when a similar product or brand is identified by the image analysis and the audio analysis.