  Often, videos are composed of multiple concepts or even genres. For instance,
news videos may contain sports, action, nature, etc. Therefore, encoding the
distribution of such concepts/genres in a compact and effective representation
is a challenging task. In this sense, we propose the Bag of Genres
representation, which is based on a visual dictionary defined by a genre
classifier. Each visual word corresponds to a region in the classification
space. The Bag of Genres video vector contains a summary of the activations of
each genre in the video content. We evaluate the proposed method for video
genre retrieval using the dataset of MediaEval Tagging Task of 2012 and for
video event retrieval using the EVVE dataset. Results show that the proposed
method achieves results comparable or superior to state-of-the-art methods,
with the advantage of providing a much more compact representation than
existing features.
