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논문 기본 정보

자료유형
학술저널
저자정보
Kyeong Hoon Jung (Kookmin University) Kang Yi (Handong Global University)
저널정보
Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.12 No.3
발행연도
2018.9
수록면
127 - 138 (12page)
DOI
10.5626/JCSE.2018.12.3.127

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초록· 키워드

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Blind spot monitoring (BSM) is one of the essential functions of Advanced Driver Assistance Systems (ADAS). In this paper, we propose a vision-based monitoring algorithm to detect vehicles in a blind-spot area using a rear-view camera. Instead of moving around the whole image to search for a vehicle, we use well-defined detection windows with fixed position and size. And we used histogram of oriented gradients (HOG) and the support vector machine (SVM) to detect a vehicle in each detection window. When a vehicle is detected, we compute the motion vector of the vehicle to determine if it approaches the ego vehicle or not. The alarm signal is finally generated based on history of events. To evaluate performance of the BSM algorithm, we captured various kinds of sequences by using a rear-view camera. Experimental results reveal precision higher than 98% and recall higher than 99%. We also develop high-speed methods to improve processing speed while keeping performance degradation as minimal as possible. Implementation of this fast algorithm on a commercial embedded device validated real-time characteristics of the proposed BSM algorithm.

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Abstract
I. INTRODUCTION
II. PROPOSED BLIND SPOT MONITORING ALGORITHM
III. HIGH-SPEED ALGORITHM FOR EMBEDDED ENVIRONMENT
IV. EXPERIMENTAL RESULTS
V. CONCLUSION
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