Fuzzy action recognition for multiple views within single camera

Chern Hong Lim, Chee Seng Chan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

To be able to perform human action recognition from multiple views is a great challenge in the field of computer vision. State-of-the-art solutions have been focusing on building a 3D action model from multiple views in a multi, calibrated cameras' environment. Promising results were achieved; however, these approaches tend to assume that human action is performed frontal-parallel to each of the multiple cameras. In a real world scenario, this is not always true and the overlapping regions in such systems are very limited. In this paper, we proposed a fuzzy action recognition framework for multiple views within a single camera. We adopted fuzzy quantity space in the framework and introduced a new concept called the Signature Action Behaviour to model an action from multiple views and represent it as fuzzy descriptor. Then, distance measure is applied to deduce an action. Experimental results showed the efficiency of our proposed framework in modeling the actions from different viewpoints and styles.

Original languageEnglish
Title of host publicationFUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventIEEE International Conference on Fuzzy Systems 2013 - Hyderabad, India
Duration: 7 Jul 201310 Jul 2013
Conference number: 22nd
https://ieeexplore.ieee.org/xpl/conhome/6612844/proceeding (Proceedings)

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

ConferenceIEEE International Conference on Fuzzy Systems 2013
Abbreviated titleFUZZ-IEEE 2013
CountryIndia
CityHyderabad
Period7/07/1310/07/13
Internet address

Keywords

  • Fuzzy action recognition
  • Fuzzy vision
  • Human activity recognition
  • View invariant motion analysis

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