TY - GEN
T1 - Sequential pattern based temporal contour representations for content-based multimedia timeline analysis
AU - Ren, Gang
AU - Johnson, Joseph
AU - Lee, Hyunhwan
AU - Ogihara, Mitsunori
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/1/31
Y1 - 2017/1/31
N2 - Temporal contour shapes are closely linked to the narrative structure of multimedia content and provide important reference points in content-based multimedia timeline analysis. In this paper, multimedia timeline is extracted from content as time varying video and audio signal features. A temporal contour representation is implemented based on sequential pattern discovery algorithm for modeling the variation contours of multimedia features. The proposed contour representation extracts repetitive temporal patterns from a hierarchy of time resolutions or from synchronized video/audio feature dimensions. The statistically significant contour components, depicting the dominant timeline shapes, are utilized as a structural or analytical representation of the timeline. The modeling performance of this proposed temporal modeling framework is demonstrated through empirical validation and subjective evaluations.
AB - Temporal contour shapes are closely linked to the narrative structure of multimedia content and provide important reference points in content-based multimedia timeline analysis. In this paper, multimedia timeline is extracted from content as time varying video and audio signal features. A temporal contour representation is implemented based on sequential pattern discovery algorithm for modeling the variation contours of multimedia features. The proposed contour representation extracts repetitive temporal patterns from a hierarchy of time resolutions or from synchronized video/audio feature dimensions. The statistically significant contour components, depicting the dominant timeline shapes, are utilized as a structural or analytical representation of the timeline. The modeling performance of this proposed temporal modeling framework is demonstrated through empirical validation and subjective evaluations.
KW - Contour representations
KW - Multimedia signal processing
KW - Multimedia structure analysis
KW - Sequential pattern
UR - http://www.scopus.com/inward/record.url?scp=85015443639&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85015443639&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2016.159
DO - 10.1109/ICMLA.2016.159
M3 - Conference contribution
AN - SCOPUS:85015443639
T3 - Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016
SP - 657
EP - 664
BT - Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016
Y2 - 18 December 2016 through 20 December 2016
ER -