Flexible and Accurate Recognition for Non-Rigid Object using Graph Matching
| Project/Area Number |
15H06009
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Perceptual information processing
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| Research Institution | Tohoku University |
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Principal Investigator |
Miyazaki Tomo 東北大学, 工学研究科, 助教 (10755101)
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| Project Period (FY) |
2015-08-28 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | グラフ認識 / 非剛体認識 / グラフ確率モデル / グラフ類似度 / 構造認識 / グラフモデル / 非剛体物体認識 / 画像認識 / 構造データ |
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| Outline of Final Research Achievements |
Graphs describe non-rigid objects which vary greatly and flexibly. However, graphs are not used for pattern recognition for image objects due to the following two problems: difficulty in extracting graphs from images and lack of a method for measuring similarity of graphs.
In this study, we propose a method for image object recognition by applying probabilistic graph model to measure similarity of graphs extracted from feature points in an image. In addition, we show the improvement of recognition performance using several probabilistic graph models. These results are significant in not only patter recognition society but also industry because a use of graphs can be facilitated by the proposed method.
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Report
(3 results)
Research Products
(4 results)
