Independent Component Analysis in Multimedia Modeling

Jan Larsen; Lars Kai Hansen; Thomas Kolenda; Finn Årup Nielsen; Shun-ichi Amari et al.

Independent Component Analysis in Multimedia Modeling

Jan Larsen, Lars Kai Hansen, Thomas Kolenda, Finn Årup Nielsen, Shun-ichi Amari et al. (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling combined text/image data for the purpose of cross-media retrieval.

Original language	English
Title of host publication	Fourth International Symposion on Independent Component Analysis and Blind Source Separation
Publication date	2003
Pages	687-696
Publication status	Published - 2003

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title = "Independent Component Analysis in Multimedia Modeling",

abstract = "Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling combined text/image data for the purpose of cross-media retrieval.",

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AB - Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling combined text/image data for the purpose of cross-media retrieval.

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