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논문 기본 정보

자료유형
학술저널
저자정보
Cuong Nguyen Manh (Korea National University of Transportation) Jaesung Lee (Korea National University of Transportation)
저널정보
한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.16 No.2
발행연도
2018.6
수록면
114 - 124 (11page)

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초록· 키워드

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This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

목차

Abstract
I. INTRODUCTION
II. SYSTEM MODEL AND METHODS
III. PERFORMANCE ESTIMATION
IV. DISCUSSION AND CONCLUSION
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