Interpretation of State Sequences in HMM for Activity Representation
Naresh P. Cuntoor, B. Yegnanarayana, Rama Chellappa · 2006
We propose a method for activity representation based on semantic events, using the HMM framework. For every time instant, the probability of event occurrence is computed by exploring a subset of state sequences. The idea is that while activity trajectories may have large variations at the data or the state levels, they may exhibit similarities at the event level. Our experiments show the application of these events to activity recognition in an office environment and to anomalous trajectory detection using surveillance video data.