Summary
Understanding human behavior in videos goes beyond recognizing objects or actions. It involves interpreting emotion, reasoning about context, and respecting privacy. Current artificial intelligence systems often rely on simple visual patterns, struggle to explain their decisions, and are trained on data that may include sensitive personal information. These limitations make it difficult to use them in real-world settings such as accessibility. This project addresses these challenges by developing methods for human-aligned video understanding that can interpret emotional and social context, pro
