| Project/Area Number |
15200008
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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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 | The University of Tokyo |
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Principal Investigator |
HIROSE Michitaka The University of Tokyo, Research Center for Advanced Science and Technology, Professor, 先端科学技術研究センター, 教授 (40156716)
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| Co-Investigator(Kenkyū-buntansha) |
HIROTA Koichi The University of Tokyo, Graduate school Frontier Sciences, Associate Professor, 大学院・新領域創成科学研究科, 助教授 (80273332)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥51,090,000 (Direct Cost: ¥39,300,000、Indirect Cost: ¥11,790,000)
Fiscal Year 2005: ¥13,910,000 (Direct Cost: ¥10,700,000、Indirect Cost: ¥3,210,000)
Fiscal Year 2004: ¥16,380,000 (Direct Cost: ¥12,600,000、Indirect Cost: ¥3,780,000)
Fiscal Year 2003: ¥20,800,000 (Direct Cost: ¥16,000,000、Indirect Cost: ¥4,800,000)
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| Keywords | Obstacle Elimination / Multi Cameras / Realtime Processing / Novel View Synthesis / Spatial Information / 実時間障害物除去 / 障害物透視映像 / 障害物透視手法 / 自然特徴点抽出 / 特徴点クラスタリング / 障害物除去映像 / 画像処理 / 画像伝送 / コンピュータビジョン / ユピキタス / ユビキタス |
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| Research Abstract |
In this study, we proposed new approach to generate novel view from which obstacles are removed by using multiple cameras. To be utilized in public environment like city, the approach should have the flexibility and scalability against the alignment of cameras. By observing the obstacle-eliminated images from any point of view, user can understand an exactly ongoing event well.
Thus, we proposed projective transformation based algorism to generate images in real time. By clustering feature points of input images and subdividing images depend on the clustered points, our algorism can be applied to scene in which obstacles are located in front of complex objects. Afterward, by morphing images based on the subdivided images, our approach can generate images from any viewpoint between cameras.
In this work, we implemented a prototype capturing system based on the approach. The system consists of management PC and many cameras and node PCs. To maintain the performance of the system, the cameras should not be manage by one PC, and therefore we use node PCs which are connected to each camera individually. All node PCs are connected with the management PC (Pentium 4 XEON 2.8GHz) through a gigabit network (1000BASE-TX).
By using this prototype system, we evaluated the performance and flexibility of the proposed method for real-time obstacle elimination. In case of several cameras, frame rate of obstacle-eliminated image is 7-10 [fps] and delay time is 160-200 [msec]. And in any patterns of camera alignments, we can eliminate obstacle from images. Also we can see the scene from any viewpoint between the camera positions while eliminating obstacles.
These results show that the proposed method can eliminate obstacle from the scene in real-time by using randomly aligned cameras. In the future, by applying the method to security cameras equipped in public environment, we can easily understand the spatial information of the scene in any time in any places.
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