Automatic video genre detection for content-based authoring

Authors:
Sung Ho Jin;Tae Meon Bae;Yong Man Ro
Affiliations:
IVY Lab., Information and Communications University (ICU), Deajeon, Korea;IVY Lab., Information and Communications University (ICU), Deajeon, Korea;IVY Lab., Information and Communications University (ICU), Deajeon, Korea
Venue:
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Year:
2004

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Low level analysis of video using spatiotemporal pixel blocks

MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security

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Abstract

In this paper, we propose a new video genre detection using semantic classification with multi-modal features. MPEG-7 audio-visual descriptors are used as multi-modal features. From the low-level multi-modal features, genre as high-level semantic meaning is detected by using GINI index in Classification And Regression Tree (CART) algorithm. Experimental results show that the proposed method is useful to detect video genre automatically with a high detection rate.