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A Movie Classifier Based on Visual Features.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Kropatsch, Walter G.
Kampel, Martin
Hanbury, Allan
Hui-Yu Huang
Weir-Sheng Shih
Source :
Computer Analysis of Images & Patterns (9783540742715); 2007, p937-944, 8p
Publication Year :
2007

Abstract

In this paper, we propose an approach to classify the film categories by using low-level features and visual features. The goal of this approach is to classify the films into genres. Our current domain of study is the movie preview. A film preview often emphasizes the theme of a film and hence provides suitable information for classification process. In our approach, we classify films into three broad categories: Action, Dramas, and Thriller films. Four computable video features (average shot length, color variance, motion content and lighting key) and visual effects are combined in our approach to provide the advantage information to demonstrate the movie category. Our approach can also be extended for other potential applications, including browsing, retrieval of videos on the internet, video-on-demand, and video libraries. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540742715
Database :
Complementary Index
Journal :
Computer Analysis of Images & Patterns (9783540742715)
Publication Type :
Book
Accession number :
33316575
Full Text :
https://doi.org/10.1007/978-3-540-74272-2_116