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- W4289205798 abstract "Identifying people's identity by using behavioral biometrics has attracted many researchers' attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. However, due to several covariates' effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. In this paper, a comprehensive overview of the existing deep learning-based gait recognition approach is presented. In addition, a summary of the performance of the approach on different gait datasets is provided." @default.
- W4289205798 created "2022-08-01" @default.
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- W4289205798 date "2022-07-29" @default.
- W4289205798 modified "2023-10-01" @default.
- W4289205798 title "Advances in Vision-Based Gait Recognition: From Handcrafted to Deep Learning" @default.
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- W4289205798 doi "https://doi.org/10.3390/s22155682" @default.
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