Frontal view gait analysis of gender

Ahmad Puad Ismail, Nooritawati Md Tahir, Aini Hussain

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

5 Citations (Scopus)

Abstract

The study aimed to investigate the potential of frontal view gait of human for gender recognition based on model based approach. Firstly, 128 features are extracted based on four parameters from the lower limb of human body specifically the left and right hip angles along with both left and right knee angles and these features are validated for gender recognition purpose. Next, statistical analysis and PSO are evaluated as feature selection in identifying the significant features amongst the original extracted gait features. Results attained with ANN as classifier proven that the original features extracted based on frontal view is capable to classify gender whilst PSO as subset selection showed promising accuracy rate with average of 85% for gender classification using the proposed front view gait technique.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012
Pages574-579
Number of pages6
DOIs
Publication statusPublished - 2013
Event2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012 - Penang
Duration: 23 Nov 201225 Nov 2012

Other

Other2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012
CityPenang
Period23/11/1225/11/12

Fingerprint

Gait analysis
Particle swarm optimization (PSO)
Set theory
Feature extraction
Statistical methods
Classifiers

Keywords

  • ANOVA
  • frontal gait
  • gender classification
  • neural network
  • PSO

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Control and Systems Engineering

Cite this

Ismail, A. P., Tahir, N. M., & Hussain, A. (2013). Frontal view gait analysis of gender. In Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012 (pp. 574-579). [6487211] https://doi.org/10.1109/ICCSCE.2012.6487211

Frontal view gait analysis of gender. / Ismail, Ahmad Puad; Tahir, Nooritawati Md; Hussain, Aini.

Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012. 2013. p. 574-579 6487211.

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

Ismail, AP, Tahir, NM & Hussain, A 2013, Frontal view gait analysis of gender. in Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012., 6487211, pp. 574-579, 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012, Penang, 23/11/12. https://doi.org/10.1109/ICCSCE.2012.6487211
Ismail AP, Tahir NM, Hussain A. Frontal view gait analysis of gender. In Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012. 2013. p. 574-579. 6487211 https://doi.org/10.1109/ICCSCE.2012.6487211
Ismail, Ahmad Puad ; Tahir, Nooritawati Md ; Hussain, Aini. / Frontal view gait analysis of gender. Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012. 2013. pp. 574-579
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