A Review on Deep Learning Classification Techniques for Gait Recognition on Humans

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Umamaheswari N, Saranya R, Shanmugapriya K

Abstract

Gait recognition is the process of identifying people based on their movements on foot or the way they walk without their co-operation or their permission. Gait is found to be less unremarkable since it can identify the person from a distance. This paper provides a review of algorithms used for classification technique in gait recognition, real-time case studies for backpropagation and SVM classifier, and recent developments in Gait recognition.Generally,a gait recognition system deals with training and testing phases. These two phases pass through different stages as pre-processing, feature extraction, and classification. The conclusion deals with the accuracy result of many classification techniques used in gait recognition, and also future directions are discussed.

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How to Cite
Umamaheswari N, Saranya R, Shanmugapriya K. (2021). A Review on Deep Learning Classification Techniques for Gait Recognition on Humans. Annals of the Romanian Society for Cell Biology, 4327–4338. Retrieved from https://www.annalsofrscb.ro/index.php/journal/article/view/5449
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