DocumentCode
261413
Title
An improved logo detection method with learning-based verification for video classification
Author
Hyo-Young Kim ; Mun-Cheon Kang ; Sung-Ho Chae ; Dae-Hwan Kim ; Sung-Jea Ko
Author_Institution
Dept. of Electron. Eng., Korea Univ., Seoul, South Korea
fYear
2014
fDate
7-10 Sept. 2014
Firstpage
192
Lastpage
193
Abstract
With the growth of cloud services, concerns have been raised regarding illegal sharing of the commercial video. To prevent the illegal sharing automatically, the method for classifying video as `commercial´ or `noncommercial´ is essentially required. Since most commercial video has a logo as a visible watermark, automatic logo detection can be an efficient method for the video classification. In this paper, we present an improved logo detection method which correctly detects the logo in any types of video using learning-based logo verification. Experimental results show that the proposed method achieves improved detection performance as compared with the existing method, and thus can be effectively used for classifying the video.
Keywords
feature extraction; image classification; video watermarking; automatic logo detection; cloud services; commercial video; learning-based verification; logo detection method; video classification; visible watermark; SVM; Video classification; copyright protection; feature extraction; logo detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics ??? Berlin (ICCE-Berlin), 2014 IEEE Fourth International Conference on
Conference_Location
Berlin
Type
conf
DOI
10.1109/ICCE-Berlin.2014.7034299
Filename
7034299
Link To Document