Automatic Movie Posters Classification into Genres (CROSBI ID 616043)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ivašić-Kos, Marina ; Pobar, Miran ; Ipšić, Ivo
engleski
Automatic Movie Posters Classification into Genres
A person can quickly grasp the movie genre (drama, comedy, cartoons, etc.) from a poster, regardless of short observation time, clutter and variety 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, visual features based on colors and structural cues are extracted from poster images and used for poster classification into genres. A single movie may belong to more than one genre (class), so the poster classification is a multi-label classification task. To solve the multi-label problem, three different types of classification methods were applied and described in this paper. These are: ML-kNN, RAKEL and Naïve Bayes. ML-kNN and RAKEL methods are directly used on multi-label data. For the Naïve Bayes the task is transformed into multiple single-label classifications. Obtained results are evaluated and compared on a poster dataset using different feature subsets. The dataset contains 6000 posters advertising films classified into 18 genres. The paper gives insights into the properties of the discussed multi-label clas-sification methods and their ability to determine movie genres from posters using low-level visual features.
multi-label classification ; data transformation method ; movie poster
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Podaci o prilogu
319-328.
2015.
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objavljeno
10.1007/978-3-319-09879-1_32
Podaci o matičnoj publikaciji
Advances in intelligent systems and computing
Madevska Bogdanova, Ana ; Gjorgjevikj, Dejan
Cham: Springer
978-3-319-09878-4
2194-5357
Podaci o skupu
Nepoznat skup
predavanje
29.02.1904-29.02.2096