@techreport{oai:ipsj.ixsq.nii.ac.jp:00232672,
 author = {柳原, 壮一郎 and 田代, 優太 and 堀田, 裕弘 and Soichiro, Yanagihara and Yuta, Tashiro and Yuukou, Horita},
 issue = {15},
 month = {Feb},
 note = {近年，都市部を中心に導入が進んでいる交通系 IC カードには，キャッシュレス化だけでなく，利用者の乗降データの収集という副次的効果があり，事業者の利用実績調査などに貢献している．しかし，IC カードを使わない利用者や IC カードを導入できない事業所での OD データは収集できていない．そこで本研究では，物体検出アルゴリズムである DeepSORT を用いた低コストかつ高精度な自動乗降者カウントシステムを提案し，その検出精度の検証や精度向上を行った．, In recent years, transportation IC cards, which have been increasingly introduced mainly in urban areas, have the secondary effect of collecting data on user boarding and alighting as well as cashless transactions, and contribute to survey s of usage performance by operators. However, OD data has not been collected from users who do not use IC cards or from offices that cannot install IC cards. Therefore, this study proposes a low-cost and highly accurate automatic passenger counting system using DeepSORT, an object detection algorithm, and verifies and improves its detection accuracy},
 title = {人物追跡を用いたバス乗降者カウントシステムの精度検証},
 year = {2024}
}