DocumentCode
1967134
Title
Movies genres classifier using neural network
Author
Jain, Sanjay K. ; Jadon, R.S.
Author_Institution
Dept. of MCA, Inst. of Technol. & Manage., Gwalior, India
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
575
Lastpage
580
Abstract
In this paper we have designed a neural network based movie genres classifier. The Movie classifier characterizes the movie clips into different movie genres. The characterization is based on low level audio-visual features. We have extracted the computable audio-visual features from the movie clips which are inspired by the techniques and film grammars used by many filmmakers to endow specific characteristics to a genre. The extracted visual features are shot length, motion, color dominance and lighting key and the extracted audio features are based on time domain, pitch, frequency domain, energy and MFCC. Movie classifier is designed using feed forward neural network with back propagation learning algorithm. We have demonstrated the effectiveness of the classifier for characterizing the movie clips into action, horror, comedy, music and drama genres.
Keywords
audio signal processing; audio-visual systems; backpropagation; cinematography; feature extraction; feedforward neural nets; humanities; image classification; video signal processing; audio feature extraction; audio-visual feature; back propagation learning algorithm; digital video; feed forward neural network; film grammar; filmmaker; movie clip; movie genre classifier; time domain; visual feature extraction; Availability; Computer network management; Feature extraction; Internet; Mood; Motion pictures; Neural networks; TV; Video compression; Video on demand; audio-visual features; movie genres classifier; neural netowrk;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Sciences, 2009. ISCIS 2009. 24th International Symposium on
Conference_Location
Guzelyurt
Print_ISBN
978-1-4244-5021-3
Electronic_ISBN
978-1-4244-5023-7
Type
conf
DOI
10.1109/ISCIS.2009.5291884
Filename
5291884
Link To Document