Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions

Mehdi Khoury; Honghai Liu

doi:10.1109/RIISS.2009.4937900

Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions

Mehdi Khoury^*
, Honghai Liu

^*Corresponding author for this work

University of Portsmouth

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

This paper introduces Fuzzy Qualitative Gaussian Inference: a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying the informationally structured space. This method is used to classify boxing moves from natural human Motion Capture data. In our experiment, the system is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that a template can be learned and a stance identified in under 18 milliseconds, which may allow recognition in real-time.

Original language	English
Title of host publication	2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings
Pages	12-18
Number of pages	7
DOIs	https://doi.org/10.1109/RIISS.2009.4937900
State	Published - 2009
Externally published	Yes
Event	2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Nashville, TN, United States Duration: 30 Mar 2009 → 2 Apr 2009

Publication series

Name	2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings

Conference

Conference	2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009
Country/Territory	United States
City	Nashville, TN
Period	30/03/09 → 2/04/09

Access to Document

10.1109/RIISS.2009.4937900

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Khoury, M., & Liu, H. (2009). Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions. In 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings (pp. 12-18). Article 4937900 (2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings). https://doi.org/10.1109/RIISS.2009.4937900

Khoury, Mehdi ; Liu, Honghai. / Fuzzy qualitative gaussian inference : Finding hidden probability distributions using fuzzy membership functions. 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings. 2009. pp. 12-18 (2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings).

@inproceedings{9e779b1a104f48ea9e1c8af5d68bd09a,

title = "Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions",

abstract = "This paper introduces Fuzzy Qualitative Gaussian Inference: a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying the informationally structured space. This method is used to classify boxing moves from natural human Motion Capture data. In our experiment, the system is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that a template can be learned and a stance identified in under 18 milliseconds, which may allow recognition in real-time.",

author = "Mehdi Khoury and Honghai Liu",

year = "2009",

doi = "10.1109/RIISS.2009.4937900",

language = "英语",

isbn = "9781424427536",

series = "2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings",

pages = "12--18",

booktitle = "2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings",

note = "2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 ; Conference date: 30-03-2009 Through 02-04-2009",

}

Khoury, M & Liu, H 2009, Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions. in 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings., 4937900, 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings, pp. 12-18, 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009, Nashville, TN, United States, 30/03/09. https://doi.org/10.1109/RIISS.2009.4937900

Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions. / Khoury, Mehdi; Liu, Honghai.
2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings. 2009. p. 12-18 4937900 (2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This paper introduces Fuzzy Qualitative Gaussian Inference: a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying the informationally structured space. This method is used to classify boxing moves from natural human Motion Capture data. In our experiment, the system is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that a template can be learned and a stance identified in under 18 milliseconds, which may allow recognition in real-time.

AB - This paper introduces Fuzzy Qualitative Gaussian Inference: a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying the informationally structured space. This method is used to classify boxing moves from natural human Motion Capture data. In our experiment, the system is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that a template can be learned and a stance identified in under 18 milliseconds, which may allow recognition in real-time.

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Khoury M, Liu H. Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions. In 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings. 2009. p. 12-18. 4937900. (2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RiiSS 2009 - Proceedings). doi: 10.1109/RIISS.2009.4937900

Fuzzy qualitative gaussian inference: Finding hidden probability distributions using fuzzy membership functions

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