Title
Cartoon Detection Using Integral
Abstract
With the growth of digital television TV program classification has become a major research topic. Recent classification techniques have reported acceptable results for specific genre detection. Cartoons is one of these genres which has deceived some attention because of its importance in push scenarios where parents want to control their children 's access to television. In this paper a flexible scheme based on a non-linear classifier called fuzzy integral is presented. This operator is supposed not only to classify but also to give a relevance measure to all the features involved in the classification. Preliminary results using this operator for cartoon detection are presented and compared with other well known statistical clarification methods like PCA, IDA or K-NN.
Year
DOI
Venue
2007
10.1109/WIAMIS.2007.28
Santorini
Keywords
Field
DocType
major research topic,specific genre detection,cartoon detection,preliminary result,acceptable result,fuzzy integral,digital television tv program,non-linear classifier,flexible scheme,recent classification technique,art,linear discriminant analysis,broadcasting,computer vision,digital television,principal component analysis,digital tv,switches,fuzzy sets
Computer vision,Broadcasting,Pattern recognition,Computer science,Fuzzy logic,Fuzzy set,Digital television,Operator (computer programming),Artificial intelligence,Linear discriminant analysis,Classifier (linguistics),Principal component analysis
Conference
ISBN
Citations 
PageRank 
0-7695-2818-X
1
0.36
References 
Authors
3
3
Name
Order
Citations
PageRank
Antonio Rama1283.93
Francesc Tarres2476.52
Laura Sanchez310.36