2003 Fiscal Year Final Research Report Summary
Research of A General Surveillance Algorithm by Images
| Project/Area Number |
14580404
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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 |
Intelligent informatics
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| Research Institution | Gunma University |
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Principal Investigator |
OHTA Naoya Gunma University, Faculty of Engineering, Professor, 工学部, 教授 (10270860)
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| Project Period (FY) |
2002 – 2003
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| Keywords | surveillance / image subtraction / geometry transformation / Homography / Wiener filter / object tracking |
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| Research Abstract |
We propose a pedestrian detection, identification, and tracking method using image information. However, since, the algorithm does not assume a particular shape of the target, this method is applicable to other targets than persons. The method consists of three stages. The first one is incoming object detection, which detects entering objects by pixel-wise operations. The second stage is pedestrian identification, which identifies individual pedestrians, and the third stage is pedestrian tracking, which tracks the position of the identified pedestrians. For the incoming object detection, we adopt a method using two cameras, which is insensitive to illumination change and shadows. One novel point of this paper is to develop a method for determining accurate geometrical transformation and calibrating camera sensitivities, which are needed for a proper operation of the incoming object detection process. The other novel point is to use a process similar to the Wiener filter, which we named regularized inverse filter, for the pedestrian identification. This improves separation of close-by pedestrians. Experiments using outdoor scenes proved that the method provided a stable detection and tracing result against the illumination change and the shadow problems. The ratio of successfully traced pedestrians was 93%.
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