Abstract
This paper represents a new technique to recognize human gait using gait flow image (GFI) and extension neural network (ENN). GFI is a gait period-based technique, based on optical flow. ENN combines the extension theory and neural networks. So a novel ENN-based gait recognition method is proposed, which outperforms all existing methods. All the study is done on, CASIA-A database, which includes 20 persons. The results derived using ENN are compared with support vector machines (SVM) and nearest neighbor (NN) classifiers. ENN proved to have 98 % accuracy and lesser iterations as compared to other traditional methods.
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Arora, P., Srivastava, S., Shivank (2016). Human Gait Recognition Using Gait Flow Image and Extension Neural Network. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 380. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2523-2_1
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DOI: https://doi.org/10.1007/978-81-322-2523-2_1
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