Abstract
A potential difficulty in digital advertising can be measuring or capitalizing on the organic exposure of physical brand sponsorships within online media content, as some systems might not analyze visual and audio content for brand presence. A multi-modal analysis engine can be used to process media content. This engine can, for example, employ computer vision to identify visual brand indicators, such as logos and products, and use automatic speech recognition and natural language processing to detect spoken brand mentions in an audio track. Detected instances of brand presence can then be converted into actionable advertising targeting criteria. Such criteria can be used to create audience or content segments for advertising platforms, which may facilitate measurement of sponsorship return on investment and support the delivery of contextually relevant advertisements to users exposed to organic brand placements.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Hijazi, Basel and Marchal, Nicolas, "Advertising Targeting Based on Multi-Modal Detection of Organic Brand Presence", Technical Disclosure Commons, (November 19, 2025)
https://www.tdcommons.org/dpubs_series/8897