Colors in multimodal data: Dominant line extraction inspired by computer vision techniques
In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correl...
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| Vydáno v: | IEEE International Geoscience and Remote Sensing Symposium proceedings s. 9 - 12 |
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| Jazyk: | angličtina |
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IEEE
01.07.2017
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| ISSN: | 2153-7003 |
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| Abstract | In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple lines in RGB color space. By extracting color lines from multimodal data, our proposed method can utilize hidden inter-channel relationships unlike conventional methods. We apply the proposed method for compressing a multimodal data matrix and show its effectiveness. |
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| AbstractList | In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple lines in RGB color space. By extracting color lines from multimodal data, our proposed method can utilize hidden inter-channel relationships unlike conventional methods. We apply the proposed method for compressing a multimodal data matrix and show its effectiveness. |
| Author | Tanaka, Yuichi Nishikawa, Tomohiro |
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| Snippet | In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor... |
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| StartPage | 9 |
| SubjectTerms | Clustering algorithms color lines compression Correlation Data mining Estimation Image color analysis Multimodal data Ocean temperature Principal component analysis sensor network sparse coding |
| Title | Colors in multimodal data: Dominant line extraction inspired by computer vision techniques |
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