CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction
Zhou, Hao1,4; Ren, Dongchun2; Yang, Xu4; Fan, Mingyu2,3; Huang, Hai1
Source PublicationPATTERN RECOGNITION
ISSN0031-3203
2023
Volume133Pages:10
Corresponding AuthorFan, Mingyu(fanmingyu@wzu.edu.cn) ; Huang, Hai(haihus@163.com)
AbstractPedestrian trajectory prediction is a key technology in many real applications such as video surveillance, social robot navigation, and autonomous driving, and significant progress has been made in this research topic. However, there remain two limitations of previous studies. First, the losses of the last time steps are heavier weighted than that of the beginning time steps in the objective function at the learning stage, causing the prediction errors generated at the beginning to accumulate to large errors at the last time steps at the inference stage. Second, the prediction results of multiple pedestrians in the prediction horizon might be socially incompatible with the interactions modeled by past trajectories. To overcome these limitations, this work proposes a novel trajectory prediction method called CSR, which consists of a cascaded conditional variational autoencoder (CVAE) module and a socially-aware regression module. The CVAE module estimates the future trajectories in a cascaded sequential manner. Specifically, each CVAE concatenates the past trajectories and the predicted location points so far as the input and predicts the adjacent location at the following time step. The socially-aware regression module generates offsets from the estimated future trajectories to produce the corrected predictions, which are more reasonable and accurate than the estimated trajectories. Experiments results demonstrate that the proposed method exhibits significant improvements over state-of-the-art methods on the Stanford Drone Dataset (SDD) and the ETH/UCY dataset of approximately 38.0% and 22.2%, respectively. The code is available at https: //github.com/zhouhao94/CSR . (c) 2022 Elsevier Ltd. All rights reserved.
KeywordPedestrian trajectory prediction Socially -aware model Conditional variational autoencoder (CVAE)
DOI10.1016/j.patcog.2022.109030
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[U21A20490] ; National Natural Science Foundation of China[61633009] ; National Natural Science Foundation of China[61973301] ; National Natural Science Foundation of China[61972020] ; National Natural Science Foundation of China[61772373] ; National Natural Science Foundation of China[51579053] ; National Natural Science Foundation of China[U1613213] ; Beijing Nova Program[Z20110 0 0 06820 046] ; Meituan Open RD Fund
Funding OrganizationNational Natural Science Foundation of China ; Beijing Nova Program ; Meituan Open RD Fund
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000861386400001
PublisherELSEVIER SCI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50407
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Corresponding AuthorFan, Mingyu; Huang, Hai
Affiliation1.Harbin Engn Univ, Natl Key Lab Sci & Technol Underwater Vehicle, Harbin, Peoples R China
2.Meituan, Res Ctr Autonomous Vehicles, Beijing, Peoples R China
3.Wenzhou Univ, Coll Comp Sci, Wenzhou, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhou, Hao,Ren, Dongchun,Yang, Xu,et al. CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction[J]. PATTERN RECOGNITION,2023,133:10.
APA Zhou, Hao,Ren, Dongchun,Yang, Xu,Fan, Mingyu,&Huang, Hai.(2023).CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction.PATTERN RECOGNITION,133,10.
MLA Zhou, Hao,et al."CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction".PATTERN RECOGNITION 133(2023):10.
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