@article{oai:ipsj.ixsq.nii.ac.jp:00017910,
 author = {杉村, 大輔 and 小林, 貴訓 and 佐藤洋一 and 杉本, 晃宏 and Daisuke, Sugimura and Yoshinori, Kobayashi and Yoichi, Sato and Akihiro, Sugimoto},
 issue = {2},
 journal = {情報処理学会論文誌コンピュータビジョンとイメージメディア（CVIM）},
 month = {Jul},
 note = {本稿では，人物の行動履歴を用いた人物追跡の安定化手法を提案する．ある決まった通路の通行，滞留などの人物の行動は，対象空間内の特定の領域で頻繁に観測される．このような人物の行動を長時間観測することにより，行動履歴に基づいた人物の存在確率分布（環境属性と定義する）を得ることができる．そしてこの環境属性をimportance functionとしてパーティクルフィルタの枠組みに組み込むことにより，安定な人物追跡，特に高速な追跡初期化を実現する．また，環境属性は毎フレーム得られる追跡結果を用いて逐次的に更新される．実環境における実験により，本手法の有効性を確認した．, We propose a method for enhancing the stability of tracking people by incorporating long-term observations of human actions in a scene. Basic human actions, such as walking or standing still, are frequently observed at particular locations in an observation scene. By observing human actions for a long period of time, we can identify regions that are more likely to be occupied by a person. These regions have a high probability of a person existing compared with others. The key idea of our approach is to incorporate this probability as a bias in generating samples under the framework of a particle filter for tracking people. We call this bias the environmental existence map (EEM). The EEM is iteratively updated at every frame by using the tracking results from our tracker, which leads to more stable tracking of people. Our experimental results demonstrate the effectiveness of our method.},
 pages = {100--110},
 title = {行動履歴に基づく人物存在確率の利用による人物三次元追跡の安定化},
 volume = {1},
 year = {2008}
}