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Mise-en-Scène Dataset: Stylistic Visual Features of Movie Trailers [dataset]

September 2016

DOI:10.13140/RG.2.1.1814.9365

Authors:

Politecnico di Bari

University of Bergen

Paolo Cremonesi

Politecnico di Milano

This dataset provides a set of 7 low-level VISUAL features extracted from 13373 movie trailers. The movie IDs are in agreement with the movie IDs provided by "MovieLens dataset", the FULL version as in July 18, 2016, containing in total 22M ratings for 33K movies. All the movie titles, ratings and associated movie genres and tags can be collected from the MovieLens website.

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Mise-en-Scene Dataset_

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Yashar Deldjoo · Mehdi Elahi · Paolo Cremonesi

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Data

Full-text available

Mise-en-Scène Dataset: Stylistic Visual Features of Movie Trailers [description]

September 2016

This dataset provides a set of 7 low-level VISUAL features extracted from 13373 movie trailers. The movie IDs are in agreement with the movie IDs provided by "MovieLens dataset", the FULL version as in July 18, 2016, containing in total 22M ratings for 33K movies. All the movie titles, ratings and associated movie genres and tags can be collected from the MovieLens website.

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May 2017

This dataset provides a set of 774 low-level VISUAL features extracted from 3964 movie trailers. The movie IDs are in agreement with the movie IDs provided by "MovieLens (ML) dataset" (ML-20M or Full Version as in May 2017). All the movie titles, ratings and associated movie genres and tags can be collected from the MovieLens website. We used the low-level MPEG-7 Low Level Feature Extraction by ... [Show full abstract] Bilkent university namely BilVideo-7 for the extraction of MPEG-7 visual features from movie trailers.

Data

Full-text available

Mise-en-Scène Dataset: MPEG-7 Visual Features of Movie Trailers [dataset]

May 2017

This dataset provides a set of 774 low-level VISUAL features extracted from 3964 movie trailers. The movie IDs are in agreement with the movie IDs provided by "MovieLens (ML) dataset" (ML-20M or Full Version as in May 2017). All the movie titles, ratings and associated movie genres and tags can be collected from the MovieLens website. We used the low-level MPEG-7 Low Level Feature Extraction by ... [Show full abstract] Bilkent university namely BilVideo-7 for the extraction of MPEG-7 visual features from movie trailers.

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Enhanced content-based multimedia recommendation method

March 2018

There is disclosed a method for generating movie recommendations, based on automatic extraction of features from a multimedia content, wherein the extracted features are visual features representing mise-en-scène characteristics of the movie defined on the basis of Applied Media Aesthetic theory, said extracted features being then fed to content-based recommendation algorithm in order to generate ... [Show full abstract] personalized recommendation.

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September 2016

Previous works have shown the effectiveness of using stylistic visual features, indicative of the movie style, in content-based movie recommendation. However, they have mainly focused on a particular recommendation scenario, i.e. , when a new movie is added to the catalogue and no information is available for that movie (New Item scenario). However , the stylistic visual features can be also used ... [Show full abstract] when other sources of information is available (Existing Item scenario). In this work, we address the second scenario and propose a hybrid technique that exploits not only the typical content available for the movies (e.g., tags), but also the stylistic visual content extracted form the movie files and fuse them by applying a fusion method called Canonical Correlation Analysis (CCA). Our experiments on a large catalogue of 13K movies have shown very promising results which indicates a considerable improvement of the recommendation quality by using a proper fusion of the stylistic visual features with other type of features.