This invention describes an automated system that reviews digital media, specifically video footage, to find and flag parts that might be considered sensitive. It works by breaking down the video into individual frames and using a machine-learning model to compare these with previously categorized content. The system then assigns sensitivity tags to these flagged sections, which can be further refined by user feedback to improve its accuracy.
Why it matters: Filed before the rapid advancements in multimodal AI and large vision models, which now offer more robust and nuanced content understanding for video analysis.
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