| Project/Area Number |
26280040
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Multimedia database
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| Research Institution | Kobe University |
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Principal Investigator |
Uehara Kuniaki 神戸大学, システム情報学研究科, 教授 (60160206)
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| Co-Investigator(Kenkyū-buntansha) |
松原 崇 神戸大学, その他の研究科, 助教 (70756197)
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| Research Collaborator |
SHIRAHAMA Kimiaki ジーゲン大学, パターン認識グループ, ポスドク
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥17,810,000 (Direct Cost: ¥13,700,000、Indirect Cost: ¥4,110,000)
Fiscal Year 2016: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2015: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2014: ¥11,440,000 (Direct Cost: ¥8,800,000、Indirect Cost: ¥2,640,000)
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| Keywords | 機械学習 / 情報検索 / 映像データ / コーパス / 映像検索 / 深層学習 |
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| Outline of Final Research Achievements |
We have developed a large-scale video retrieval method that can identify videos relevant to a semantically high-level query (e.g., “playing a guitar outdoors), by combing recognition results of concepts (abstracted names of meanings that a human can perceive from a video). Despite the recent advancement of concept detection, it is still difficult to accurately recognise various concepts. Thus, based on Dempster-Shafer Theory, we have quantised uncertainties in concept detection, and developed a probabilistic method that can perform accurate retrieval even using uncertain (erroneous) concept detection results. In addition, by adopting a visual attention model, we have developed a video retrieval method that reflects user’s intention by considering which concepts attract his/her attention.
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