Movie posters classification into genres based on low-level features

Author

Ivasic-Kos, Marina ; Pobar, M. ; Mikec, L.

Author_Institution

Dept. of Inf., Univ. of Rijeka, Rijeka, Croatia

fYear

2014

fDate

26-30 May 2014

Firstpage

1198

Lastpage

1203

Abstract

A person can quickly grasp the genre (drama, comedy, cartoons, etc.) from a movie poster, regardless of visual clutter and the level of details. Bearing this in mind, it can be assumed that simple properties of a movie poster should play a significant role in automated detection of movie genres. Therefore, low-level features based on colors and edges are extracted from poster images and used for poster classification into genres. In this paper, poster classification is modeled as a multilabel classification task, where a single movie may belong to more than one class (genre). To simplify and solve the multilabel problem, two methods for multi-label data transformation are described and evaluated given the classification results obtained by distance ranking, Naïve Bayes and RAKEL. Experiments are conducted on a set of 1500 posters with 6 movie genres. Results provide insights into the properties of the discussed algorithms and features.

Keywords

Bayes methods; edge detection; feature extraction; humanities; image classification; image colour analysis; Naïve Bayes; RAKEL; automated movie genre detection; colors; distance ranking; edges; low-level feature extraction; low-level features; movie posters classification; multilabel classification task; multilabel data transformation; poster classification; poster images; visual clutter; Animation; Feature extraction; Histograms; Image color analysis; Image edge detection; Motion pictures; Visualization; data transformation method; movie poster; multi-label classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on

Conference_Location

Opatija

Print_ISBN

978-953-233-081-6

Type

conf

DOI

10.1109/MIPRO.2014.6859750

Filename

6859750