2013 Fiscal Year Final Research Report
Video Retrieval System based on Machine Learning
| Project/Area Number |
23300038
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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 | 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) |
SHIRAHAMA Kimiaki 日本学術振興会, 海外特別研究員 (30467675)
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| Project Period (FY) |
2011-04-01 – 2014-03-31
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| Keywords | マルチメディア / 機械学習 / 映像データ / 映像検索 |
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| Research Abstract |
Query-By-Example (QBE) can be considered as a machine learning problem. Here, given videos for a query, a classifier is built to discriminate between relevant and irrelevant videos based on features like color, edge and motion. This research has explored QBE from the perspectives of machine learning, such as training examples, features, learning algorithms and data size. As a result, we have developed a fast and accurate method which can retrieve videos relevant to a query from a large amount video data. Furthermore, by applying the developed method to object recognition, we have achieved the highest performance at TRECVID 2012 that is a NIST-sponsored annual worldwide competition on video analysis.
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