Multimedia information fusion.
Information in the ubiquitous media age is typically fragmented and appears in various unstructured and unlabelled fonns as data, text, image, audio, and video. For transforming raw information content into knowledge, there is a need to develop various cross-media and media-specific technologies fo...
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| Format: | Thesis |
| Language: | English |
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2010
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| Online Access: | http://hdl.handle.net/10356/41506 |
| _version_ | 1826127646465982464 |
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| author | Woon, Kia Yan. |
| author2 | Tan Ah Hwee |
| author_facet | Tan Ah Hwee Woon, Kia Yan. |
| author_sort | Woon, Kia Yan. |
| collection | NTU |
| description | Information in the ubiquitous media age is typically fragmented and appears in various
unstructured and unlabelled fonns as data, text, image, audio, and video. For transforming raw information content into knowledge, there is a need to develop various cross-media and media-specific technologies for modeling and working with text, audio, image, and video data as well as their unification and association at the semantic level. As part of the research
endeavor of the 12R-SCE, NTU joint project, "Intelligent Technologies for Media Analysis, Representation and Fusion (Intelligent Media)", this dissertation aims to contribute the techniques for information fusion. Following a thorough research of the literature review on the related work, this dissertation presents a self-organizing network model known as fusion Adaptive Resonance Theory (fusion ART) for the fusion of multimedia infonnation. By synchronizing the encoding of infonnation across multiple media channels, the fusion ART model generates clusters that encode the associative mappings among multimedia
information in a real-time and continuous manner. The fusion ART's functionalities are
illustrated through experiments on two multimedia data sets, namely the terrorist domain data set and Corel data set. In the experiments using the terrorist domain data set, it demonstrates that by incorporating a semantic category channel, fusion ART further enables multi-media infonnation to be fused into predefined themes or semantic categories. In the experiments using the Corel data set, the results suggest the viability of the proposed approach in
comparison with other prior work in image annotations, image classification and image-text fusion. |
| first_indexed | 2024-10-01T07:11:58Z |
| format | Thesis |
| id | ntu-10356/41506 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:11:58Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/415062019-12-10T12:03:18Z Multimedia information fusion. Woon, Kia Yan. Tan Ah Hwee Wee Kim Wee School of Communication and Information DRNTU::Social sciences::Mass media Information in the ubiquitous media age is typically fragmented and appears in various unstructured and unlabelled fonns as data, text, image, audio, and video. For transforming raw information content into knowledge, there is a need to develop various cross-media and media-specific technologies for modeling and working with text, audio, image, and video data as well as their unification and association at the semantic level. As part of the research endeavor of the 12R-SCE, NTU joint project, "Intelligent Technologies for Media Analysis, Representation and Fusion (Intelligent Media)", this dissertation aims to contribute the techniques for information fusion. Following a thorough research of the literature review on the related work, this dissertation presents a self-organizing network model known as fusion Adaptive Resonance Theory (fusion ART) for the fusion of multimedia infonnation. By synchronizing the encoding of infonnation across multiple media channels, the fusion ART model generates clusters that encode the associative mappings among multimedia information in a real-time and continuous manner. The fusion ART's functionalities are illustrated through experiments on two multimedia data sets, namely the terrorist domain data set and Corel data set. In the experiments using the terrorist domain data set, it demonstrates that by incorporating a semantic category channel, fusion ART further enables multi-media infonnation to be fused into predefined themes or semantic categories. In the experiments using the Corel data set, the results suggest the viability of the proposed approach in comparison with other prior work in image annotations, image classification and image-text fusion. Master of Science (Information Studies) 2010-07-16T01:29:29Z 2010-07-16T01:29:29Z 2008 2008 Thesis http://hdl.handle.net/10356/41506 en Nanyang Technological University 79 p. application/pdf |
| spellingShingle | DRNTU::Social sciences::Mass media Woon, Kia Yan. Multimedia information fusion. |
| title | Multimedia information fusion. |
| title_full | Multimedia information fusion. |
| title_fullStr | Multimedia information fusion. |
| title_full_unstemmed | Multimedia information fusion. |
| title_short | Multimedia information fusion. |
| title_sort | multimedia information fusion |
| topic | DRNTU::Social sciences::Mass media |
| url | http://hdl.handle.net/10356/41506 |
| work_keys_str_mv | AT woonkiayan multimediainformationfusion |