2001 Fiscal Year Final Research Report Summary
Tracking of multiple persons in a wide area by partial information obtained from distributed active cameras
| Project/Area Number |
11450161
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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 |
Measurement engineering
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| Research Institution | Osaka University |
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Principal Investigator |
SHIRAI Yoshiaki Professor, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 教授 (50206273)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMADA Nobutaka Research Associate, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助手 (10294034)
MIURA Jun Associate Professor, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助教授 (90219585)
KUNO Yoshinori Professor, Department of Engineering, Saitama University, 工学研究科, 教授 (10252595)
SASAKI Shigeru Director, Multimedia System Laboratory, Fujitsu Laboratories, マルチメディアシステム研究所, 研究職
SAKIYAMA Takuro Research Associate, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助手 (70335371)
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| Project Period (FY) |
1999 – 2001
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| Keywords | distributed vision / tracking / face identification / face detection / cooperation / uncertainty / probablistic model / keyword 8 |
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| Research Abstract |
We studied a method of multiple person tracking by processing images taken from distributed cameras in a wide space, and that of discriminating persons by identifying the face. The main results are the followings:
1. Research theme 1: We have developed a method of person tracking by optical flow obtained from an image sequence. Then we have developed a method of probabilistic estimation of person positions based on the color changes learned in a learning phase.
2. Research theme 2: We have developed a method of detecting faces based on face parts such as eyes and nose in candidate areas of the face. We clarified that the uncertainty of the face identification depends on the face direction in a obtained image, and developed a probabilistic model of uncertainty of identification.
3. Research theme 3: We have formalized how to estimate information of a person obtained before leaving the scene. We then defined the evaluation function, for determining where to look, in terms of information obtained so far and estimated information obtained in future.
4. Research theme 4: We have developed a method to determine parameters of the probabilistic model of information obtained in the scene by a recursive simulation.
5. Research theme 5: We have constructed a PC cluster system and made experiments of real time monitoring of persons by distributed processing of the PC cluster.
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