Automated recognition of highly complex human behavior

Alvin Harvey Kam, Toh Kar Ann, Eng How Lung, Yau Wei Yun, Wang Junxian

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

4 Citations (Scopus)

Abstract

We describe a framework for automated complex human behavior recognition, illustrating important concepts with specific examples drawn from our work on a unique platform designed to understand water crises related behaviors in a public swimming pool. We argue for a hierarchical representation, leveraging on quantitative descriptors to model a behaviour's intermediate semantics. Complex behaviour inference is then demonstrated using a novel regression-based approach based on a modified version of a functional link network which learns quickly and classifies accurately in comparison with other competing decision making schemes.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages327-330
Number of pages4
DOIs
Publication statusPublished - 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 2004 Aug 232004 Aug 26

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period04/8/2304/8/26

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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