대한임베디드공학회논문지 (IEMEK Journal of Embedded Systems and Applications)

대한임베디드공학회 (Institute of Embedded Engineering of Korea)
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Refinement Module 기반 Three-Scale 보행자 검출 기법

A Three-scale Pedestrian Detection Method based on Refinement Module

  • 투고 : 2023.04.06
  • 심사 : 2023.07.16
  • 발행 : 2023.10.31
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초록

Pedestrian detection is used to effectively detect pedestrians in various situations based on deep learning. Pedestrian detection has difficulty detecting pedestrians due to problems such as camera performance, pedestrian description, height, and occlusion. Even in the same pedestrian, performance in detecting them can differ according to the height of the pedestrian. The height of general pedestrians encompasses various scales, such as those of infants, adolescents, and adults, so when the model is applied to one group, the extraction of data becomes inaccurate. Therefore, this study proposed a pedestrian detection method that fine-tunes the pedestrian area by Refining Layer and Feature Concatenation to consider various heights of pedestrians. Through this, the score and location value for the pedestrian area were finely adjusted. Experiments on four types of test data demonstrate that the proposed model achieves 2-5% higher average precision (AP) compared to Faster R-CNN and DRPN.

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과제정보

본 논문은 문화체육관광부 및 한국콘텐츠진흥원의 2022년도 문화체육관광 연구개발사업으로 수행되었음 (과제명: 인지·신체 복합중재 재활운동 증강 디바이스 기술 개발, 과제번호: SR202106002, 기여울: 100%).

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