@article {12675, title = {Interpretation of state sequences in HMM for activity representation}, journal = {Proc. IEEE Conf. Acoustic Speech and Signal Processing}, volume = {2}, year = {2005}, month = {2005///}, pages = {709 - 712}, abstract = {We propose a method for activity representation based on seman-tic 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 ex- hibit similarities at the event level. Our experiments show the ap- plication of these events to activity recognition in an office envi- ronment and to anomalous trajectory detection using surveillance video data. }, author = {Cuntoor, N.P. and Yegnanarayana,B. and Chellapa, Rama} }