반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

딥러닝 기반의 자동차 분류 및 추적 알고리즘

Vehicle Classification and Tracking based on Deep Learning

  • 안효창 ((주)이앤에이치) ;
  • 이용환 (원광대학교 디지털콘텐츠공학과)
  • 투고 : 2023.09.14
  • 심사 : 2023.09.18
  • 발행 : 2023.09.30
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초록

One of the difficult works in an autonomous driving system is detecting road lanes or objects in the road boundaries. Detecting and tracking a vehicle is able to play an important role on providing important information in the framework of advanced driver assistance systems such as identifying road traffic conditions and crime situations. This paper proposes a vehicle detection scheme based on deep learning to classify and tracking vehicles in a complex and diverse environment. We use the modified YOLO as the object detector and polynomial regression as object tracker in the driving video. With the experimental results, using YOLO model as deep learning model, it is possible to quickly and accurately perform robust vehicle tracking in various environments, compared to the traditional method.

키워드

과제정보

본 연구는 2023년도 정부(미래창조과학부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(과제번호: 2021R1A2C1012947).

참고문헌

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