Human activity analysis based on a torso-less representation

Jen-Hui Chuang*, Chun Wei Lee, Kuo Hua Lo

*Corresponding author for this work

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

2 Scopus citations

Abstract

Human activity recognition is a popular topic in the field of computer vision. While most analysis algorithms take into consideration of the whole human body, the movements of merely the head and limbs are often informative enough in many practical applications. In this paper, a novel approach is proposed to track these extruding parts of a human body in consecutive images. Accordingly, a simplified torso-less pattern of gesture is proposed to represent human activities, and with its effectiveness verified subjectively by some experimental results. Such a representation can not only ensure the privacy of the person being watched, but is also suitable for real-time surveillance based on bandwidth-limited communication since only a very small amount of data are used compared to conventional approaches.

Original languageEnglish
Title of host publication2008 19th International Conference on Pattern Recognition, ICPR 2008
DOIs
StatePublished - 1 Dec 2008
Event2008 19th International Conference on Pattern Recognition, ICPR 2008 - Tampa, FL, United States
Duration: 8 Dec 200811 Dec 2008

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference2008 19th International Conference on Pattern Recognition, ICPR 2008
CountryUnited States
CityTampa, FL
Period8/12/0811/12/08

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    Chuang, J-H., Lee, C. W., & Lo, K. H. (2008). Human activity analysis based on a torso-less representation. In 2008 19th International Conference on Pattern Recognition, ICPR 2008 [4761030] (Proceedings - International Conference on Pattern Recognition). https://doi.org/10.1109/ICPR.2008.4761030