A
system and method for
contextual advertising that analyzes video content through multimodal examination of visual, audio, and textual elements to create detailed contextual understanding of individual scenes. The
system segments video content into discrete scenes and simultaneously processes each scene to extract contextual characteristics including objects, settings, dialogue, music, and emotional tone. These characteristics are classified according to advertising industry taxonomies and converted into numerical embeddings that enable
semantic similarity matching. During video playback, when advertisement opportunities occur, the
system identifies the current scene context, analyzes available advertisements using similar techniques, computes similarity scores between scene and advertisement characteristics, and selects contextually appropriate advertisements for seamless integration. This approach enables privacy-compliant advertising that matches advertisement content with scene context rather than relying solely on user
behavioral data, improving advertisement relevance and viewer experience.