深層学習を用いた午睡中の乳幼児の頭部検出と頭の向き推定

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2023/09/01

タイトル(英語): Head Detection and Head Orientation Estimation of Infants during a Nap using Deep Learning

著者名: 廣瀬　誠（松江工業高等専門学校 情報工学科）

著者名(英語): Makoto Hirose (Information Technology, National Institute of Technology, Matsue College)

キーワード: 頭部検出，頭の向き推定，乳幼児，うつ伏せ寝，深層学習　　head detection，head orientation estimation，infant，face down position，deep learning

要約(英語): In this paper, we describe head detection and pose estimation of infants sleeping in a nursery school. Every year, there are many cases of infants dying from put in a prone sleeping position during nap time. Because a nursery teacher cares for several infants, and even if they pay attention, they cannot check on the condition of all the infants. We have been working on the development of a system that attaches a camera to the ceiling to take video of infants, detects infants of face down position, and sends alerts to the smartphone of a nursery teacher. Pose estimation focusing only on the infant's head cannot use existing methods for estimating face orientation because the infant's face may not be in the video. Therefore, we propose a two-step method for head detection and head orientation estimation. For head detection and head orientation estimation, YOLOv5 and VGG-16 with deep learning are employed to create a head detector and a head orientation estimator. Based on the experimental results, we will compare the accuracy of head detection and head orientation estimation with conventional methods, and verify their usefulness in the system.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.143 No.9 （2023） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 871-876 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/143/9/143_871/_article/-char/ja/