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Pregled bibliografske jedinice broj: 709099

Movie posters classification into genres based on low-level features


Ivašić-Kos, Marina; Pobar, Miran; Mikec, Luka
Movie posters classification into genres based on low-level features // Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) / Biljanović, Petar (ur.).
Rijeka: Croatian Society for Information and Communication Technology, Electronics and Microelectronics - MIPRO, 2014. str. 1448-1453 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Movie posters classification into genres based on low-level features

Autori
Ivašić-Kos, Marina ; Pobar, Miran ; Mikec, Luka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) / Biljanović, Petar - Rijeka : Croatian Society for Information and Communication Technology, Electronics and Microelectronics - MIPRO, 2014, 1448-1453

ISBN
978-953-233-078-6

Skup
International Convention on Information and Communication Technology, Electronics and Microelectronics (37 ; 2014)

Mjesto i datum
Opatija, Hrvatska, 26-30.05.2014

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Multi-label classification ; data transformation method ; movie poster

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekt / tema
318-0361935-0852 - Govorne tehnologije (Ivo Ipšić, )
Prirodna
višemodalna komunikacija čovjek stroj

Ustanove
Sveučilište u Rijeci - Odjel za informatiku