DocumentCode :
2552168
Title :
Support Vector Machines Content-Based Video Retrieval based solely on Motion Information
Author :
Zampoglou, Markos ; Papadimitriou, Theophilos ; Diamantaras, Konstantinos I.
Author_Institution :
Univ. of Macedonia, Thessaloniki
fYear :
2007
fDate :
27-29 Aug. 2007
Firstpage :
176
Lastpage :
180
Abstract :
A new content-based video shot classification method for the purpose of retrieval is proposed, based on the Perceived Motion Energy Spectrum (PMES) descriptor and Support Vector Machines. Using only motion features, we demonstrate the method´s success in learning to separate team sports video shots from all the other videos using real-world material from a TV channel´s archive. We show both the PMES descriptor´s ability to characterize a video shot, and the clear potential of training an SVM to classify any given video into a category, thus moving one more step towards automatic labeling of video.
Keywords :
content-based retrieval; image classification; image motion analysis; indexing; support vector machines; video retrieval; content-based video retrieval; perceived motion energy spectrum descriptor; support vector machine; video shot classification method; Content based retrieval; Feature extraction; Image retrieval; Indexing; Informatics; Information retrieval; Multimedia databases; Support vector machine classification; Support vector machines; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2007 IEEE Workshop on
Conference_Location :
Thessaloniki
ISSN :
1551-2541
Print_ISBN :
978-1-4244-1566-3
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2007.4414302
Filename :
4414302
Link To Document :
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