Development of Image Retrieval System by Considering People Co-occurrence Relations through Relevance Feedback
| Project/Area Number |
23700117
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Media informatics/Database
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| Research Institution | Osaka University |
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Principal Investigator |
NITTA Naoko 大阪大学, 工学(系)研究科(研究院), 講師 (00379132)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2012: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2011: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 人物画像検索 / 適合性フィードバック / 共起関係 / クラス分類 / 能動学習 / 構造化 / 人物の共起関係 |
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| Research Abstract |
Group photos often contain socially related people such as family and friends. We developed a system for retrieving images containing a specific target person from a group photo collection by considering people co-occurrence relations. A Bag of People (BoP) feature, which represents both the facial appearances of persons and their co-occurrence relations, is extracted from each image. By using the BoP features, a classifier for classifying images into two classes, images containing the target person and other images, can be trained. The images determined to contain the target person by the classifier are presented to the user as the retrieval results. The classifier is re-trained by a small number of correctly retrieved images which are selected by the user. When retrieving images of 32 persons from 1791 group photos, the mean average precision improved from 20% to 70% after five feedback iterations.
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Report
(4 results)
Research Products
(10 results)
