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2006 IEEE International Conference on Multimedia and Expo
Recognizing Commercials in Real-Time using Three Visual Descriptors and a Decision-Tree
Toronto, ON, Canada
July 09-July 12
ISBN: 1-4244-0366-7
ASCII Text
x 
 
Ronald Glasberg, Cengiz Tas, Thomas Sikora, "Recognizing Commercials in Real-Time using Three Visual Descriptors and a Decision-Tree," Multimedia and Expo, IEEE International Conference on, pp. 1481-1484, 2006 IEEE International Conference on Multimedia and Expo, 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICME.2006.262822,
author = {Ronald Glasberg and Cengiz Tas and Thomas Sikora},
title = {Recognizing Commercials in Real-Time using Three Visual Descriptors and a Decision-Tree},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2006},
isbn = {1-4244-0366-7},
pages = {1481-1484},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2006.262822},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - Recognizing Commercials in Real-Time using Three Visual Descriptors and a Decision-Tree
SN - 1-4244-0366-7
SP1481
EP1484
A1 - Ronald Glasberg,
A1 - Cengiz Tas,
A1 - Thomas Sikora,
PY - 2006
KW - null
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
Ronald Glasberg, Communication Systems Group, Technical University Berlin, 10587 Berlin, Germany. glasberg@nue.tu-berlin.de
Cengiz Tas, Communication Systems Group, Technical University Berlin, 10587 Berlin, Germany. ctas@cs.tu-berlin.de
Thomas Sikora, Communication Systems Group, Technical University Berlin, 10587 Berlin, Germany. sikora@nue.tu-berlin.de
We present a new approach for classifying mpeg-2 video sequences as `commercial' or `non-commercial' by analyzing specific color, texture and motion features of consecutive frames in real-time. This is part of the well-known video-genre-classification problem, where popular TV-broadcast genres like cartoon, commercial, music, news and sports are studied. Such applications have also been discussed in the context of MPEG-7 [11]. In our method the extracted features from three visual descriptors are logically combined using a decision tree to produce a reliable recognition. The results demonstrate a high identification rate based on a large collection of 200 representative video sequences (40 `commercials' and 4*40 `non-commercials') gathered from free digital TV-broadcasting in Germany.
Citation:
Ronald Glasberg, Cengiz Tas, Thomas Sikora, "Recognizing Commercials in Real-Time using Three Visual Descriptors and a Decision-Tree," icme, pp.1481-1484, 2006 IEEE International Conference on Multimedia and Expo, 2006
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