Automatic recognition of film genres
Proceedings of the third ACM international conference on Multimedia
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
MM '09 Proceedings of the 17th ACM international conference on Multimedia
On the use of computable features for film classification
IEEE Transactions on Circuits and Systems for Video Technology
Video genre classification using weighted kernel logistic regression
Advances in Multimedia - Special issue on Multimedia Applications for Smart Device in Ubiquitous Environments
Film segmentation and indexing using autoassociative neural networks
International Journal of Speech Technology
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This paper presents a method for movie genre categorization of movie trailers, based on scene categorization. We view our approach as a step forward from using only low-level visual feature cues, towards the eventual goal of high-level seman- tic understanding of feature films. Our approach decom- poses each trailer into a collection of keyframes through shot boundary analysis. From these keyframes, we use state-of- the-art scene detectors and descriptors to extract features, which are then used for shot categorization via unsuper- vised learning. This allows us to represent trailers using a bag-of-visual-words (bovw) model with shot classes as vo- cabularies. We approach the genre classification task by mapping bovw temporally structured trailer features to four high-level movie genres: action, comedy, drama or horror films. We have conducted experiments on 1239 annotated trailers. Our experimental results demonstrate that exploit- ing scene structures improves film genre classification com- pared to using only low-level visual features.