A graph based multimodal geospatial interpolation framework

Mengfan Tang, Pranav Agrawal, Feiping Nie, Siripen Pongpaichet, Ramesh Jain

科研成果: 书/报告/会议事项章节会议稿件同行评审

8 引用 (Scopus)

摘要

Recent multimedia research has increasingly focused on large scale multimodal data from disparate geospatial sensors. In addition to the volume of the data, the diversity and granularity of the data poses a major challenge in extracting meaningful and actionable information. To address this, we present a novel spatial interpolation framework, capable of incorporating multimodal data sources and modeling the spatial processes comprehensively at multiple resolutions. The framework transforms the spatial interpolation problem into a graph structure learning problem, based on the latent structure of the data. This enables more efficient and accurate predictions at unobserved locations. We demonstrate the effectiveness of our approach by testing it on air pollution interpolation.

源语言英语
主期刊名2016 IEEE International Conference on Multimedia and Expo, ICME 2016
出版商IEEE Computer Society
ISBN(电子版)9781467372589
DOI
出版状态已出版 - 25 8月 2016
活动2016 IEEE International Conference on Multimedia and Expo, ICME 2016 - Seattle, 美国
期限: 11 7月 201615 7月 2016

出版系列

姓名Proceedings - IEEE International Conference on Multimedia and Expo
2016-August
ISSN(印刷版)1945-7871
ISSN(电子版)1945-788X

会议

会议2016 IEEE International Conference on Multimedia and Expo, ICME 2016
国家/地区美国
Seattle
时期11/07/1615/07/16

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