| Co-Investigator(Kenkyū-buntansha) |
FUSE Takashi Japan Society for the Promotion of Science, Reserch Fellow, 特別研究員(PD)
TSUTSUML Morito Graduate School of Engineering, Assistant Professor, 大学院・工学系研究科, 講師 (70292886)
MORICHI Shigeru Graduate School of Engineering, Professor, 大学院・工学系研究科, 教授 (40016473)
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| Research Abstract |
1. Review of optical flow estimation methods
Optical flow estimation methods in all pixels are divided into gradient-based approach and area-based approach. The basic methods of the gradient-based approach are increase in the number of observation equations and imposition of a condition. The area-based approach has cross correlation, sequential similarity detection, eigen window.
2. Comparison of their performance empirically from the point of view of application to vehicle motion analysis
The reviewed methods were applied to sequential images from fixed video cameras and high altitude video cameras. The result showed the difficulty of estimation of precise and dense optical flow by ordinary gradient-based approaches. On the other hand, the results by SSDA were better than gradient-based approach.
3. Development of vehicle recognition method
With features, that are value of background subtraction and optical flow, all pixels in a spatio-temporal image are clustered. The spatio-temporal clustering means unifying pixels which meet homogeneous property.
4. Application to real sequential images
The proposed method was applied to 10cm and 1/30sec sequential images. In this experiment 77 vehicles in all, whose movements include direct advances, left and right-hand turns, lane changes and stoppage, could be recognized.
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