Group Event Detection with a Varying Number of Group Members for Video Surveillance

28 Feb 2015  ·  Weiyao Lin, Ming-Ting Sun, Radha Poovendran, Zhengyou Zhang ·

This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. We propose to use a group representative to handle the recognition with a varying number of group members, and use an Asynchronous Hidden Markov Model (AHMM) to model the relationship between people... Furthermore, we propose a group activity detection algorithm which can handle both symmetric and asymmetric group activities, and demonstrate that this approach enables the detection of hierarchical interactions between people. Experimental results show the effectiveness of our approach. read more

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here