Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph

S. Shahbudin, Aini Hussain, Ahmed El-Shafie, N. M. Tahir, Salina Abdul Samad

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

5 Citations (Scopus)

Abstract

In this paper, a neuro-fuzzy technique known as the Adaptive-Neuro Fuzzy Inference System (ANFIS) has been used to highlight the application of ANFIS to perform human posture classification task using the new simplified shock graph (SSG) representation. Basically, a shock graph is a shape abstraction that decomposed a shape into a set of hierarchically organized primitive parts. The shock graph that represents the silhouette of an object in terms of a set of qualitatively defined parts and organized in a hierarchical, directed acyclic graph is used as a powerful representation of human shape in our work. The SSG feature provides a compact, unique and simple way of representing human shape and has been tested with several classifiers. As such, in this paper we intend to test its efficacy with another classifier, that is, the ANFIS classifier system. The result showed that the proposed ANFIS model can be used in classifying various human postures.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages585-595
Number of pages11
Volume5857 LNCS
DOIs
Publication statusPublished - 2009
Event1st International Visual Informatics Conference, IVIC 2009 - Kuala Lumpur
Duration: 11 Nov 200913 Nov 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5857 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Visual Informatics Conference, IVIC 2009
CityKuala Lumpur
Period11/11/0913/11/09

Fingerprint

Adaptive Neuro-fuzzy Inference System
Fuzzy inference
Shock
Classifiers
Classifier
Graph in graph theory
Graph Representation
Silhouette
Neuro-fuzzy
Directed Acyclic Graph
Efficacy
Human

Keywords

  • Adaptive-Neuro Fuzzy Inference System (ANFIS)
  • Artificial Neural Network (ANN)
  • Simplified shock graph (SSG)

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Shahbudin, S., Hussain, A., El-Shafie, A., Tahir, N. M., & Abdul Samad, S. (2009). Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5857 LNCS, pp. 585-595). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS). https://doi.org/10.1007/978-3-642-05036-7_55

Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph. / Shahbudin, S.; Hussain, Aini; El-Shafie, Ahmed; Tahir, N. M.; Abdul Samad, Salina.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS 2009. p. 585-595 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS).

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

Shahbudin, S, Hussain, A, El-Shafie, A, Tahir, NM & Abdul Samad, S 2009, Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5857 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5857 LNCS, pp. 585-595, 1st International Visual Informatics Conference, IVIC 2009, Kuala Lumpur, 11/11/09. https://doi.org/10.1007/978-3-642-05036-7_55
Shahbudin S, Hussain A, El-Shafie A, Tahir NM, Abdul Samad S. Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS. 2009. p. 585-595. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-05036-7_55
Shahbudin, S. ; Hussain, Aini ; El-Shafie, Ahmed ; Tahir, N. M. ; Abdul Samad, Salina. / Adaptive-neuro fuzzy inference system for human posture classification using a simplified shock graph. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS 2009. pp. 585-595 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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