Face Information Structuring Based on Data Mining from Large-Scale Broadcast Video Archive
| Project/Area Number |
22700113
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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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 |
WU Xiaomeng 国立情報学研究所, コンテンツ科学研究系, 特任研究員 (20462179)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | マルチメディア / 画像,文章,音声等認識 / 画像、文章、音声等認識 |
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| Research Abstract |
In this project, we achieved a higher-level facial recognition and structuration technique based on the integration of visual information and broadcasting metadata. The technique was applied to a large-scale broadcast video archive with broadcasting metadata of great variety. While proposing a facial image matching algorithm robust against the variation in illumination condition, pose, and expression, we formulated the classic facial recognition task into a quantitative prediction problem that estimates the event probability of cause-effect relationship accompanied by network path. The solution was achieved in the form of a novel facial classification approach based on a Bayesian network constructed on top of broadcasting metadata, which leverages the correlation between the broadcasting metadata and the broadcast video in a both effective and efficient manner.
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Report
(4 results)
Research Products
(6 results)
