TY - JOUR
T1 - An integrated music video browsing system for personalized television
AU - Kim, Hyoung Gook
AU - Kim, Jin Young
AU - Baek, Jun Geol
N1 - Funding Information:
This work was supported by Korea Research Foundation Grant funded by the Korean Government ( KRF-2008-331-D00421 ) and by the Research Grant of Kwangwoon University in 2008.
Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011/1
Y1 - 2011/1
N2 - In this paper, we propose an integrated music video browsing system for personalized digital television. The system has the functions of automatic music emotion classification, automatic theme-based music classification, salient region detection, and shot classification. From audio (music) tracks, highlight detection and emotion classification are performed on the basis of information on temporal energy, timbre and tempo. For video tracks, shot detection is fulfilled to classify shots into face shots and color-based shots. Lastly automatic grouping of themes is executed on music titles and their lyrics. With a database of international music videos, we evaluate the performance of each function implemented in this paper. The experimental results show that the music browsing system achieves remarkable performances. Thus, our system can be adopted in any digital television for providing personalized services.
AB - In this paper, we propose an integrated music video browsing system for personalized digital television. The system has the functions of automatic music emotion classification, automatic theme-based music classification, salient region detection, and shot classification. From audio (music) tracks, highlight detection and emotion classification are performed on the basis of information on temporal energy, timbre and tempo. For video tracks, shot detection is fulfilled to classify shots into face shots and color-based shots. Lastly automatic grouping of themes is executed on music titles and their lyrics. With a database of international music videos, we evaluate the performance of each function implemented in this paper. The experimental results show that the music browsing system achieves remarkable performances. Thus, our system can be adopted in any digital television for providing personalized services.
KW - Highlight detection
KW - Music emotion classification
KW - Music video browsing
KW - Shot classification
KW - Theme-based music classification
UR - http://www.scopus.com/inward/record.url?scp=77956603878&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956603878&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2010.07.032
DO - 10.1016/j.eswa.2010.07.032
M3 - Article
AN - SCOPUS:77956603878
VL - 38
SP - 776
EP - 784
JO - Expert Systems with Applications
JF - Expert Systems with Applications
SN - 0957-4174
IS - 1
ER -