In group activity recognition, the temporal dynamics of the whole activity can be inferred based on the dynamics of the individual people representing the activity. We build a deep …
S Yi, H Li, X Wang - Proceedings of the IEEE conference on …, 2015 - openaccess.thecvf.com
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 …
J Shao, C Change Loy, X Wang - Proceedings of the IEEE …, 2014 - openaccess.thecvf.com
Groups are the primary entities that make up a crowd. Understanding group-level dynamics and properties is thus scientifically important and practically useful in a wide range of …
B Zhou, X Tang, X Wang - Proceedings of the IEEE …, 2013 - openaccess.thecvf.com
Collective motions are common in crowd systems and have attracted a great deal of attention in a variety of multidisciplinary fields. Collectiveness, which indicates the degree of …
S Yi, H Li, X Wang - Computer Vision–ECCV 2016: 14th European …, 2016 - Springer
In this paper, a deep neural network (Behavior-CNN) is proposed to model pedestrian behaviors in crowded scenes, which has many applications in surveillance. A pedestrian …
B Zhou, X Tang, X Wang - International Journal of Computer Vision, 2015 - Springer
Collective behaviors characterize the intrinsic dynamics of the crowds. Automatically understanding collective crowd behaviors has important applications to video surveillance …
Modern crowd theories agree that collective behavior is the result of the underlying interactions among small groups of individuals. In this work, we propose a novel algorithm …
The local feature based approaches have become popular for activity recognition. A local feature captures the local movement and appearance of a local region in a video, and thus …
To obtain a more comprehensive activity understanding for a crowded scene, in this paper, we propose a new problem of panoramic human activity recognition (PAR), which aims to …