HMM-based segmentation and recognition of human activities from video sequences

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

58 Scopus citations

Abstract

Recognizing human activities from image sequences is an active area of research in computer vision. Most of the previous work on activity recognition focuses on recognition from video clips that show only single activities. There are few published algorithms for segmenting and recognizing complex activities that are composed of more than one single activity. In this paper, we present a novel HMM-based approach that uses threshold and voting to automatically and effectively segment and recognize complex activities. Experiments on a database of video clips of different activities show that our method is effective.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Multimedia and Expo, ICME 2005
Pages804-807
Number of pages4
DOIs
StatePublished - Dec 1 2005
EventIEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands
Duration: Jul 6 2005Jul 8 2005

Publication series

NameIEEE International Conference on Multimedia and Expo, ICME 2005
Volume2005

Other

OtherIEEE International Conference on Multimedia and Expo, ICME 2005
CountryNetherlands
CityAmsterdam
Period7/6/057/8/05

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Niu, F., & Abdel-Mottaleb, M. (2005). HMM-based segmentation and recognition of human activities from video sequences. In IEEE International Conference on Multimedia and Expo, ICME 2005 (pp. 804-807). [1521545] (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005). https://doi.org/10.1109/ICME.2005.1521545