Pedestrian Behavior Modeling From Stationary Crowds With Applications to Intelligent Surveillance
Publication in refereed journal


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摘要Pedestrian behavior modeling and analysis is important for crowd scene understanding and has various applications in video surveillance. Stationary crowd groups are a key factor influencing pedestrian walking patterns but was mostly ignored in the literature. It plays different roles for different pedestrians in a crowded scene and can change over time. In this paper, a novel model is proposed to model pedestrian behaviors by incorporating stationary crowd groups as a key component. Through inference on the interactions between stationary crowd groups and pedestrians, our model can be used to investigate pedestrian behaviors. The effectiveness of the proposed model is demonstrated through multiple applications, including walking path prediction, destination prediction, personality attribute classification, and abnormal event detection. To evaluate our model, two large pedestrian walking route datasets are built. The walking routes of around 15 000 pedestrians from two crowd surveillance videos are manually annotated. The datasets will be released to the public and benefit future research on pedestrian behavior analysis and crowd scene understanding.
著者Yi S, Li HS, Wang XG
期刊名稱IEEE Transactions on Image Processing
出版年份2016
月份9
日期1
卷號25
期次9
出版社IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
頁次4354 - 4368
國際標準期刊號1057-7149
電子國際標準期刊號1941-0042
語言英式英語
關鍵詞crowd video surveillance; Pedestrian behavior modeling; stationary crowd groups
Web of Science 學科類別Computer Science; Computer Science, Artificial Intelligence; Engineering; Engineering, Electrical & Electronic

上次更新時間 2021-28-02 於 01:40