Yahoo Labs' Algorithm Identifies Creativity in 6-Second Vine Videos | MIT Technology Review: ".... They then analysed each video with various algorithms. For example, they looked for compositional features such as the rule of thirds and shallow depth of field. They used an algorithm for analysing the content of video scenes that studies the contours and layout in an image. They also looked for any evidence that the videos were stop motion animations or designed to run on a seemingly endless loop by looking for similarities between the first and last frame. And they assessed the novelty of each video by comparing its properties against a randomly selected group of others.
They then looked for correlations between the features found by machine algorithms and the videos identified as creative by human volunteers. It turns out that the scene content is most strongly correlated with creativity, followed by compositional features and video novelty.
In a final step, they trained a machine learning algorithm to use these features to find creative videos in a dataset it had not seen before. That algorithm was able to correctly classify videos as either creative or noncreative 80 per cent of the time.
That’s an interesting result that opens the possibility of automatically filtering the Vine livestream for the most creative content. “This allows us to study audio-visual creativity at a fine-grained level, helping us to understand what, exactly, constitutes creativity in micro-videos,” say Redi and co.
And if it is possible for an algorithm to identify creativity accurately, why wouldn’t it be possible for a computer to generate creative content? In fact, spotting the difference between human-produced creativity and computer generated creativity may one day be an interesting Turing test-style exercise." (read more at link above)
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