人間の動作軌跡予測に関するサーベイ
Human Motion Trajectory Prediction: A Survey
自動運転やサービスロボットなどに向けた人間の動作軌跡予測研究を、運動モデリング手法と文脈情報の利用レベルで分類し、データセットや評価指標も整理したサーベイ論文。
著者: Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M. Kitani, Dariu M. Gavrila, Kai O. Arras
分類: cs.RO, cs.CV, cs.LG
原文アブストラクト
With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.
