On the influence of low-level visual features in film classification.

ABSTRACT:

Background

In this paper we present a model of parameters to aesthetically characterize films using a multi-disciplinary approach: by combining film theory, visual low-level video descriptors (modeled in order to supply aesthetic information) and classification techniques using machine and deep learning.

Methods

Four different tests have been developed, each for a different application, proving the model's usefulness. These applications are: aesthetic style clustering, prediction of production year, genre detection and influence on film popularity.

Results

The results are compared against high-level information to determine the accuracy of the model to classify films without knowing such information previously. The main difference with other film characterization appr

SUBMITTER: Alvarez F 

PROVIDER: S-EPMC6386315 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature