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Automated gait-based gender identification using fuzzy local binary patterns with tuned parameters

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Abstract

With the rapid advances in sensor networks and internet-of-things, several applications have evolved to ubiquitously monitor what is happening in smart environments. This paper designs a gait-based gender identification system based on an improved method of fuzzy local binary patterns for texture analysis. The moving person’s silhouette is extracted and a texture image is constructed to summarize structural and dynamical variations over one gait cycle. Then, histograms representing soft pattern variations are constructed and used as feature vectors. The proposed method employs grid search to find the optimal hyper-parameters for the feature extraction method. Finally, support vector machines are trained to predict the gender of the walking person. The performance is evaluated and compared with four other local binary pattern (LBP) related texture descriptors. The results show significant improvements in the performance under different walking conditions.

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Acknowledgements

The authors would like to thank King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, and Hadhramout Establishment for Human Development (HEHD), Yemen, for their support during this work.

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Authors and Affiliations

  1. Information and Computer Science Department, College of Computer Sciences and Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    E.-S. M. El-Alfy & A. G. Binsaadoon

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  1. E.-S. M. El-Alfy
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  2. A. G. Binsaadoon
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Correspondence to E.-S. M. El-Alfy.

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El-Alfy, ES.M., Binsaadoon, A.G. Automated gait-based gender identification using fuzzy local binary patterns with tuned parameters. J Ambient Intell Human Comput 10, 2495–2504 (2019). https://doi.org/10.1007/s12652-018-0728-0

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  • DOI: https://doi.org/10.1007/s12652-018-0728-0

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