@techreport{oai:ipsj.ixsq.nii.ac.jp:00113454,
 author = {石井, 淳 and 倉沢, 央 and 佐藤, 浩史 and 中村, 元紀 and 高須, 淳宏 and 相原, 健郎 and 安達, 淳 and Jun, Ishii and Hisashi, Kurasawa and Hiroshi, Sato and Motonori, Nakamura and Atsuhiro, Takasu and Kenro, Aihara and Jun, Adachi},
 issue = {32},
 month = {Feb},
 note = {人の位置情報に基づく適切なサービスを提供するためには精度の高い測位技術が求められる．一般に誤差を含む測位情報を修正するための手法としてはカルマンフィルタやパーテイクルフィルタが用いられるが，これらの手法は時系列的な変化を考慮に入れるのみで個々の人物が持つ属性や環境の変化が考慮されることはない．そこで本研究では多量の歩行者データから人物の移動に影響を与える属性の分析を行い，得られた属性情報をパーティクルフィルタに組み込む手法を提案する．, High-accuracy position estimation systems are needed for providing a service customized for each person based on their position information. In order to estimate a precise position from the observed position containing some errors, the Kalman filter and the particle filter are frequently used. However, these filters are only taking time series information into account. Each person's attribute and transition of environment, which would be also effective to revise location information, are never considered. In this paper, we analyzed attribute which effects one's moving route and propose a method for building these attribute information to the particle filter.},
 title = {属性情報を利用した歩行者測位情報フィルタリング手法の提案},
 year = {2015}
}