Model learning for image understanding from video archives
| Project/Area Number |
17300040
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | National Institute of Informatics |
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Principal Investigator |
SATOH Shin'ichi National Institute of Informatics, Digital Content and Media Sciences Research Division, Professor (90249938)
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| Co-Investigator(Kenkyū-buntansha) |
MICHAEL E Houle National Institute of Informatics, Collaborative Research Unit, Visiting Professor (90399270)
KATAYAMA Norio National Institute of Informatics, Digital Content and Media Sciences Research Division, Associate Professor (60280559)
HIROSHI Mo National Institute of Informatics, Digital Content and Media Sciences Research Division, Assistant Professor (60312203)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥16,750,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2007: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2006: ¥5,300,000 (Direct Cost: ¥5,300,000)
Fiscal Year 2005: ¥5,600,000 (Direct Cost: ¥5,600,000)
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| Keywords | Image indexing / Image mining / Image recognition model / Clustering / Multimodal analysis |
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| Research Abstract |
In this study, we address techniques to automatically learn models for image understanding from everyday broadcast video. This is especially useful to realize video content analysis for video archive retrieval and to realize robot vision for interactive robot supporting daily life.
For these purposes, it is not necessary to realize very precise visual measurement which is typically used for industrial robots, however, it is desired to identify many various types of objects which ordinary people know as the common sense, or to identify new object which might become new trend. The main goal of the study is to establish the methodology to automatically and dynamically obtain image understanding models from broadcast videos.
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Report
(4 results)
Research Products
(98 results)
