| Project/Area Number |
14350206
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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 |
情報通信工学
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| Research Institution | Keio University |
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Principal Investigator |
OZAWA Shinji Keio University, Faculty of Science and Technology, Professor, 理工学部, 教授 (70051761)
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| Co-Investigator(Kenkyū-buntansha) |
SAITO Hideo Keio University, Faculty of Science and Technology, Associate Professor, 理工学部, 助教授 (90245605)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥11,400,000 (Direct Cost: ¥11,400,000)
Fiscal Year 2004: ¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2003: ¥3,800,000 (Direct Cost: ¥3,800,000)
Fiscal Year 2002: ¥4,100,000 (Direct Cost: ¥4,100,000)
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| Keywords | sequential image processing / detection of moving object / optimal view point / scene analysis / game analysis / オクルージョン |
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| Research Abstract |
In this research, to realize an interactive broadcasting is aimed. Soccer video is concerned as example, and sequential images from optionally assigned view direction, are generated automatically. When object is sports which is played in large fields like soccer, it is very much difficult to capture by one camera for whole scene. However many cameras are used, only one selected camera is selected by expert and broadcasted. So automatic camera selection systems yield to viewers demand are desired. This is called an interactive video generation systems. The results are as follows,
To construct an environments of image capture from multi-camera Many cameras are fixed around the soccer field and those images are analyzed. Camera for broadcasting will be controlled by the results of analysis.
Detection and tracking of players and ball using image sequence from multi-camera To detect a ball in one frame, template matching technique are applied, and to detect players, background difference images are used. After that, inter frame tracking algorithms are proposed and applied. The algorithms are well worked and useful to make loci of players.
To develop an algorithm for error correction caused by occluded player When a player is occluded by other player in image from one camera. An occlusion should not exist in images from the other camera, or be estimated players and ball position.
To decide the best view direction Information from tracking of ball and player are concerned to feature value. The analysis of those feature value vector, gives the best view direction
To recognize play type Players around the ball are detected, position and velocity information are used for distinguish soccer play such as pass, shot tackle and so on
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