Study of techniques for motion image retrieval based on motion information
| Project/Area Number |
12650367
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
情報通信工学
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
YOSHIDA Toshiyuki Graduate school of sci. and eng., Assoc. Prof., 理工学研究科, 助教授 (50240297)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 2001: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2000: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Motion image / MPEG / Motion vector / Retrieval / MPEG |
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| Research Abstract |
In this research, we aimed at developing techniques for retrieving MPEG-encoded motion images based mainly on motion information. The following are the results of the research :
1. We selected a sketch-based, feature-based model for the target retrieval system. For the feature values, we used histograms of the average color and motion vector for each macroblock.
2. Taking the histogram of the color and motion vector in a video scene drops their spatio-temporal distribution information. In order to maintain the information as well as to speed up the retrieval, we proposed a hierarchical matching technique.
3. We obtained the result that a representation of motion vectors in a kind of polar coordinate system rather than in the orthogonal coordinate gives an efficient similarity measure for motion vectors which well match human visual characteristics. We then actually applied the similarity measure to the motion image retieval and confirmed its efficiency over the conventional orthogonal coordinate representation.
4. The matching algorithm based on motion vector and color histograms requires the users to input all the information with respect to the foreground and background objects and camera motions for the target scene. Since this is, however, not always possible, we have revised the algorithm in such a way that a histogram matching can be performed without knowing all the information for the target scene.
5. We combined all the fundamental algorithms developed in this research to make a prototype retrieval system for motion images. Numbers of retrieval experiments on the prototype system have confirmed that the system can search for scences that are close to user's target scenes.
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Report
(3 results)
Research Products
(21 results)
