A Synchronous Bi-Directional Framework With Temporally Dependent Interaction Modeling for Pedestrian Trajectory Prediction

As an essential part of motion behavior modeling, pedestrian trajectory forecasting with social interactions has become an increasingly important problem in many applications, such as visual navigation and intelligent video surveillance. Most existing methods adopt autoregressive frameworks to forec...

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Veröffentlicht in:	IEEE transactions on network science and engineering 2024-01, Vol.11 (1), p.1-14
Hauptverfasser:	Li, Yuanman, Xie, Ce, Liang, Rongqin, Du, Jie, Zhou, Jiantao, Li, Xia
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Behavioral sciences Bidirectional control deep networks Forecasting Interaction models Mathematical models Modelling Motion behavior modeling Pedestrians Prediction algorithms Predictions Predictive models social behaviors Social factors Social interaction social interactions Task analysis Trajectories Trajectory trajectory prediction
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