Advances in Gait-Based Identification

A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques
Erscheinungsjahr 2026
ISBN: 978-3-031-89562-3
Verlag: Springer

Buch, Englisch, Band 593, 96 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 189 g

Reihe: Studies in Systems, Decision and Control

This book provides a systematic review of gait-based person identification, categorizing studies into deep-learning and non-deep-learning approaches while analyzing key datasets and performance metrics. It explores challenges such as covariant factors, e.g., viewing angles, clothing, and accessories, and highlights advancements in real-world gait recognition systems. With a structured methodology and transparent review process, this work serves as a valuable reference for researchers and a foundation for future developments in biometric identification.

Zielgruppe

Research

Autoren/Hrsg.

Bastos, Diogo R. M.

R. S. Tavares, João Manuel

Fachgebiete

• Naturwissenschaften Physik Angewandte Physik Biophysik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung

Inhaltsverzeichnis

Introduction.- Background.- Research objectives and method.- Datasets.- Comparison of the reviewed methods.- Conclusion.

Über Autor(innen)

Diogo R. M. Bastos holds an MSc in biomedical engineering from the Faculdade de Engenharia da Universidade do Porto (FEUP). His research interests include artificial intelligence, computer vision, and gait-based biometric identification.

João Manuel R. S. Tavares is a Full Professor in the Department of Mechanical Engineering at the Faculdade de Engenharia da Universidade do Porto (FEUP) and a senior researcher at the Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial (INEGI). His research focuses on computational vision, medical imaging, biomechanics, and biomedical engineering.