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Proceedings Paper

Geometric moments for gait description
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Paper Abstract

The optical flow associated with a set of digital images of a moving individual is analyzed in order to extract a gait signature. For this, invariant Hu moments are obtained for image description. A Hu Moment History (HMH) is obtained from K frames to describe the gait signature of individuals in a video. The gait descriptors are subsequences of the HMH of variable width. Each subsequence is generated by means of genetic algorithms and used for classification in a neuronal network. The database for algorithm evaluation is MoBo, and the gait classification results are above 90% for the cases of slow and fast walking and 100% for the cases of walking with a ball and inclined walking. An optical processor is also implemented in order to obtain the descriptors of the human gait.

Paper Details

Date Published: 26 September 2013
PDF: 8 pages
Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 88561H (26 September 2013); doi: 10.1117/12.2024666
Show Author Affiliations
C. Toxqui-Quitl, Univ. Politécnica de Tulancingo (Mexico)
V. Morales-Batalla, Univ. Politécnica de Tulancingo (Mexico)
A. Padilla-Vivanco, Univ. Politécnica de Tulancingo (Mexico)
C. Camacho-Bello, Univ. Politécnica de Tulancingo (Mexico)


Published in SPIE Proceedings Vol. 8856:
Applications of Digital Image Processing XXXVI
Andrew G. Tescher, Editor(s)

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