Interpretation of state sequences in HMM for activity representation

Naresh P. Cuntoor, B. Yegnanarayana, Rama Chellappa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
PagesII709-II712
DOIs
StatePublished - 2005
Externally publishedYes
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeII
ISSN (Print)1520-6149

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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