Research of Robust Algorithm for Understanding a Situation in a Dynamic Environment
| Project/Area Number |
17500103
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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 |
Perception information processing/Intelligent robotics
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| Research Institution | Hirosaki University |
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Principal Investigator |
ONOGUCHI Kazunori Hirosaki University, Faculty of Science and Technology, Professor, 理工学部, 教授 (40374813)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2006: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2005: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | moving object detection / bad visibility / video surveillance / intensity histogram / cross correlation / stereopsis / sunshine change / shadow elimination / 視程 / 分散 / Temporal Templates / 動作認識 / 動画像 |
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| Research Abstract |
1.Robust object detection algorithm toward sunshine change and a shadow
"Planar Projection Stereopsis Method" is effective to eliminate shadow areas casted by moving objects. However, this method has a major problem that it detects not only moving objects but also road areas occluded by objects in one image. In this research, this problem has been solved by conceiving new algorithm for eliminating occluded areas, comparing contours of areas detected by the planar projection stereopsis method with edges in an original image.
2.Robust moving object detection algorithm in bad weather
In the weather whose visibility is bad, such as in a snowfall or in a dense fog, the visibility changes rapidly in a short time and the intensity of each pixel changes hard every frame. In order to overcome these problems, the proposed algorithm divides an input image into grid regions and in each region, calculates a cross correlation between two histograms whose accumulated number of frames are different. A short accumulated histogram, generated from accumulating a few number of frames, changes quickly whenever moving objects go into the region. On the other hand, a long accumulated histogram, generated from accumulating the more number of frames, changes slowly. Therefore, moving objects are detected by measuring a variation on a cross correlation between a short accumulated histogram and a long accumulated histogram.
3.Algorithm for measuring visibility from image sequences
The proposed algorithm divides an input image into grid regions and solves the degree of the snowfall or darkness by measuring the change of intensity variance in each region.
4.Gesture recognition algorithm using stereo image sequences
A gesture recognition method extending Temporal Templates so that they can contain not only vertical and horizontal motion but also depth information obtained from a binocular stereopsis has been conceived.
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Report
(3 results)
Research Products
(9 results)
