Geometric moments for gait description

C. Toxqui-Quitl; V. Morales-Batalla; A. Padilla-Vivanco; C. Camacho-Bello

doi:10.1117/12.2024666

26 September 2013 Geometric moments for gait description

C. Toxqui-Quitl, V. Morales-Batalla, A. Padilla-Vivanco, C. Camacho-Bello

Proceedings Volume 8856, Applications of Digital Image Processing XXXVI; 88561H (2013) https://doi.org/10.1117/12.2024666
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

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.

Citation Download Citation

C. Toxqui-Quitl, V. Morales-Batalla, A. Padilla-Vivanco, and C. Camacho-Bello "Geometric moments for gait description", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 88561H (26 September 2013); https://doi.org/10.1117/12.2024666

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