Deep Structured Models For Group Activity Recognition [article]

Zhiwei Deng, Mengyao Zhai, Lei Chen, Yuhao Liu, Srikanth Muralidharan, Mehrsan Javan Roshtkhari, Greg Mori
2015 arXiv   pre-print
This paper presents a deep neural-network-based hierarchical graphical model for individual and group activity recognition in surveillance scenes. Deep networks are used to recognize the actions of individual people in a scene. Next, a neural-network-based hierarchical graphical model refines the predicted labels for each class by considering dependencies between the classes. This refinement step mimics a message-passing step similar to inference in a probabilistic graphical model. We show that
more » ... this approach can be effective in group activity recognition, with the deep graphical model improving recognition rates over baseline methods.
arXiv:1506.04191v1 fatcat:43bmyn46zbgthliyctn67h2que