Pedestrian Trajectory Prediction in Extremely Crowded Scenarios

Pedestrian Trajectory Prediction in Extremely Crowded Scenarios

Pedestrian trajectory prediction under crowded circumstances is a challenging problem owing to human interaction and the complexity of the trajectory pattern. Various methods have been proposed for solving this problem, ranging from traditional Bayesian analysis to Social Force model and deep learni...

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Bibliographic Details
Main Authors: Xiaodan Shi, Xiaowei Shao, Zhiling Guo, Guangming Wu, Haoran Zhang, Ryosuke Shibasaki
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Sensors
Subjects:
trajectory prediction
human interaction
LSTM
crowded scenarios
encoder–decoder model
deep learning
Online Access:http://www.mdpi.com/1424-8220/19/5/1223

Internet

http://www.mdpi.com/1424-8220/19/5/1223

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