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In this talk you will explore the invisible side of visual data, investigating how machine learning can detect subjective properties of images and videos, such as beauty, creativity, sentiment, style, and more curious characteristics.
See how these detectors can be applied in the context of web media search, advertising and social media, and analyse the precious contribution of computer vision in understanding how people and cultures perceive visual properties, underlining the importance of feature interpretability for this task.
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The Science of Visual Interactions
Miriam Redi is a Research Scientist in the Social Dynamics team at Bell Labs Cambridge. Her research focuses on content-based social multimedia understanding and culture analytics. In particular, she explores ways to automatically assess visual aesthetics, sentiment and creativity, and exploit the power of computer vision in the context of web, social media, and online communities.