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Journal of Applied Sciences
  Year: 2006 | Volume: 6 | Issue: 2 | Page No.: 419-424
DOI: 10.3923/jas.2006.419.424
 
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Eigenposture for Classification

Nooritawati Md Tahir, Aini Hussain , Salina Abdul Samad , Hafizah Husain and Mohd Marzuki Mustafa

Abstract:
This study outlines a mechanism for human body posture classification based on various combination of eigenspace transform which we named as `eigenposture` using three different classifiers; the Multilayer Perceptron (MLP), Nearest Neighbour (NN) and Probabilistic Neural Network (PNN). We apply principal component transformation to extract the features from human shape silhouettes. A combination of them was used to classify the posture of standing and non standing based on the human shape obtained from segmentation process. Different classifiers are compared to each other with respect to classification performance. Results show that combination of second and fourth eigenpostures outperformed the other eigenpostures combination.
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How to cite this article:

Nooritawati Md Tahir, Aini Hussain , Salina Abdul Samad , Hafizah Husain and Mohd Marzuki Mustafa , 2006. Eigenposture for Classification. Journal of Applied Sciences, 6: 419-424.

DOI: 10.3923/jas.2006.419.424

URL: https://scialert.net/abstract/?doi=jas.2006.419.424

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