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딥러닝 기반 객체 인식을 활용한 퍼스널 모빌리티 안전 보조 시스템 개발
곽현서,김민영,전지용,정은혜,김주엽,현소담,정진우 한국정보통신학회 2021 한국정보통신학회논문지 Vol.25 No.3
Recently, the demand for the use of personal mobility vehicles, such as an electric kickboard, is increasing explosively because of its high portability and usability. However, the number of traffic accidents caused by personal mobility vehicles has also increased rapidly in recent years. To address the issues regarding the driver’s safety, we propose a novel approach that can monitor context information around personal mobility vehicles using deep learning-based object detection and smartphone captured videos. In the proposed framework, a smartphone is attached to a personal mobility device and a front or rear view is recorded to detect an approaching object that may affect the driver's safety. Through the detection results using YOLOv5 model, we report the preliminary results and validated the feasibility of the proposed approach.