Datasets column: predicting the emotional impact of movies

Affective video content analysis aims at the automatic recognition of emotions elicited by videos. It has a large number of applications, including mood based personalized content recommendation, video indexing, and efficient movie visualization and browsing. Beyond the analysis of existing video material, affective computing techniques can also be used to generate new content, e.g., movie summarization, personalized soundtrack recommendation to make user-generated videos more attractive. Affective techniques can furthermore be used to enhance the user engagement with advertising content by optimizing the way ads are inserted inside videos.