CineScale: A dataset of cinematic shot scale in movies.

CNN Close up Film studies Frames Long shot Medium shot Movies Shot scale Video analysis

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Jun 2021
Historique:
received: 16 12 2020
revised: 11 03 2021
accepted: 22 03 2021
entrez: 17 5 2021
pubmed: 18 5 2021
medline: 18 5 2021
Statut: epublish

Résumé

We provide a database containing shot scale annotations (i.e., the apparent distance of the camera from the subject of a filmed scene) for more than 792,000 image frames. Frames belong to 124 full movies from the entire filmographies by 6 important directors: Martin Scorsese, Jean-Luc Godard, Béla Tarr, Federico Fellini, Michelangelo Antonioni, and Ingmar Bergman. Each frame, extracted from videos at 1 frame per second, is annotated on the following scale categories: Extreme Close Up (ECU), Close Up (CU), Medium Close Up (MCU), Medium Shot (MS), Medium Long Shot (MLS), Long Shot (LS), Extreme Long Shot (ELS), Foreground Shot (FS), and Insert Shots (IS). Two independent coders annotated all frames from the 124 movies, whilst a third one checked their coding and made decisions in cases of disagreement. The CineScale database enables AI-driven interpretation of shot scale data and opens to a large set of research activities related to the automatic visual analysis of cinematic material, such as the automatic recognition of the director's style, or the unfolding of the relationship between shot scale and the viewers' emotional experience. To these purposes, we also provide the model and the code for building a Convolutional Neural Network (CNN) architecture for automated shot scale recognition. All this material is provided through the project website, where video frames can also be requested to authors, for research purposes under fair use.

Identifiants

pubmed: 33997191
doi: 10.1016/j.dib.2021.107002
pii: S2352-3409(21)00286-9
pmc: PMC8090997
doi:

Types de publication

Journal Article

Langues

eng

Pagination

107002

Informations de copyright

© 2021 The Author(s).

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.

Références

Psychophysiology. 2007 Sep;44(5):680-6
pubmed: 17584187
Atten Percept Psychophys. 2016 Apr;78(3):891-901
pubmed: 26728045
Psychon Bull Rev. 2016 Dec;23(6):1713-1743
pubmed: 27142769
Front Psychol. 2018 Jan 17;8:2349
pubmed: 29387032

Auteurs

Mattia Savardi (M)

Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy.

András Bálint Kovács (AB)

Film Department, ELTE University, Budapest, Hungary.

Alberto Signoroni (A)

Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy.

Sergio Benini (S)

Department of Information Engineering, University of Brescia, via Branze 38, 25123, Brescia, Italy.

Classifications MeSH