Holistic LSTM for Pedestrian Trajectory Prediction

Accurate predictions of future pedestrian trajectory could prevent a considerable number of traffic injuries and improve pedestrian safety. It involves multiple sources of information and real-time interactions, e.g. , vehicle speed and ego-motion, pedestrian intention and historical locations. Exis...

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Veröffentlicht in:	IEEE transactions on image processing 2021, Vol.30, p.3229-3239
Hauptverfasser:	Quan, Ruijie, Zhu, Linchao, Wu, Yu, Yang, Yi
Format:	Artikel
Sprache:	eng
Schlagworte:	Correlation Dynamics holistic LSTM Information sources Injury prevention Logic gates long short-term memory Pedestrian crossings pedestrian intention Pedestrian safety Pedestrian trajectory prediction Pedestrians Rescaling Roads Task analysis Traffic safety Traffic speed Trajectories Trajectory Vehicle dynamics Vehicles
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