DocumentCode :
3401668
Title :
Gait recognition system tailored for Arab costume of the Gulf region
Author :
Shanableh, Tamer ; Assaleh, Khaled ; Hajjaj, Layla Ai ; Kabani, AbdulWahab
Author_Institution :
Dept. of Comput. Sci. & Eng., American Univ. of Sharjah, Sharjah, United Arab Emirates
fYear :
2009
fDate :
14-17 Dec. 2009
Firstpage :
544
Lastpage :
549
Abstract :
Existing work on gait recognition is focused on casual (western) customs hence not suitable for the gulf region where long gowns are used for both men and women. This paper proposes a gait recognition solution that is suitable for both gulf customs and casual customs. The solution is based on computing an adaptive image prediction between consecutive images. The resultant predictions are then accumulated into one image and transformed using either discrete cosine transformation (DCT) or Radon transformation. The feature vectors of the gait are computed from such transformed images. Feature modeling based on polynomial networks follows. The proposed solution is tested on a dataset with around 100 participants with mixed genders and mixed customs. The proposed system yields an impressive classification rates approaching 100% accuracy.
Keywords :
Radon transforms; adaptive signal processing; discrete cosine transforms; gait analysis; gender issues; image recognition; polynomials; vectors; Arab costume; Radon transformation; adaptive image prediction; casual customs; discrete cosine transformation; feature modeling; feature vectors; gait recognition system; gender; gulf customs; gulf region; polynomial networks; Adaptive filters; Computational complexity; Computational modeling; Educational institutions; Electrocardiography; Least squares approximation; Noise cancellation; Signal to noise ratio; Steady-state; Vectors; Human identification; computer vision; gait biometric; motion analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology (ISSPIT), 2009 IEEE International Symposium on
Conference_Location :
Ajman
Print_ISBN :
978-1-4244-5949-0
Type :
conf
DOI :
10.1109/ISSPIT.2009.5407511
Filename :
5407511
Link To Document :
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