Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques

Bastos, Diogo R. M./ Tavares, Joćo Manuel R. S.

ISBN 10: 3031895592 / ISBN 13: 9783031895593

Published by Springer-Nature New York Inc, 2025

About this Item

115 pages. 9.25x6.10x9.21 inches. In Stock.

Seller Inventory # x-3031895592

Bibliographic Details

• Title: Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques
• Publisher: Springer-Nature New York Inc
• Publication Date: 2025
• Language: English
• ISBN 10: 3031895592
• ISBN 13: 9783031895593
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.35 kilograms

About this title

Synopsis

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.

About the Author

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.

Joćo 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 Ciźncia e Inovaēćo em Engenharia Mecānica e Engenharia Industrial (INEGI). His research focuses on computational vision, medical imaging, biomechanics, and biomedical engineering.