Human Gait Recognition using Deep Learning: A Comprehensive Review
Muhammad Imran Sharif Mehwish Mehmood Muhammad Irfan Sharif Md Palash Uddin
Gait recognition (GR) is a growing biometric modality used for person
identification from a distance through visual cameras. GR provides a secure and
reliable alternative to fingerprint and face recognition, as it is harder to
distinguish between false and authentic signals. Furthermore, its resistance to
spoofing makes GR suitable for all types of environments. With the rise of deep
learning, steadily improving strides have been made in GR technology with
promising results in various contexts. As video surveillance becomes more
prevalent, new obstacles arise, such as ensuring uniform performance evaluation
across different protocols, reliable recognition despite shifting lighting
conditions, fluctuations in gait patterns, and protecting privacy.This survey
aims to give an overview of GR and analyze the environmental elements and
complications that could affect it in comparison to other biometric recognition
systems. The primary goal is to examine the existing deep learning (DL)
techniques employed for human GR that may generate new research opportunities.