Right Inflight?

A Dataset for Exploring the Automatic Prediction of Movies Suitable for a Watching Situation

Conference paper (2016)

Authors

M.A. Riegler Universitetet i Oslo
Concetto Spampinato University of Catania
Pål Halvorsen Universitetet i Oslo
Mathias Lux University of Klagenfurt
Jonas Markussen Universitetet i Oslo
Konstantin Pogorelov Universitetet i Oslo
Carsten Griwodz Universitetet i Oslo
Håkon Stensland Universitetet i Oslo
Context Multimedia Intent Data Set
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Published Date

2016-5

Language

English

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Abstract

In this paper, we present the dataset Right Inflight developed to support the exploration of the match between video content and the situation in which that content is watched. Specifically, we look at videos that are suitable to be watched
on an airplane, where the main assumption is that that viewers watch movies with the intent of relaxing themselves and letting time pass quickly, despite the inconvenience and discomfort of flight. The aim of the dataset is to support the
development of recommender systems, as well as computer vision and multimedia retrieval algorithms capable of automatically predicting which videos are suitable for inflight consumption. Our ultimate goal is to promote a deeper understanding of how people experience video content, and of how technology can support people in finding or selecting video content that supports them in regulating their internal states in certain situations. Right Inflight consists of 318
human-annotated movies, for which we provide links to trailers, a set of pre-computed low-level visual, audio and text features as well as user ratings. The annotation was performed by crowdsourcing workers, who were asked to judge
the appropriateness of movies for inflight consumption.