Advances in Gait-Based Identification : A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques / by Diogo R. M. Bastos, João Manuel R. S. Tavares.

Format:

Book

Author/Creator:

Bastos, Diogo R. M., Author.

R. S. Tavares, João Manuel., Author.

Series:

Studies in Systems, Decision and Control, 2198-4190 ; 593

Language:

English

Subjects (All):

Computer vision.

Image processing.

Biomechanics.

Artificial intelligence.

Biometric identification.

Computer Vision.

Image Processing.

Artificial Intelligence.

Biometrics.

Local Subjects:

Computer Vision.

Image Processing.

Biomechanics.

Artificial Intelligence.

Biometrics.

Physical Description:

1 online resource (XIX, 96 p. 22 illus., 18 illus. in color.)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

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.

Contents:

Introduction

Background

Research objectives and method

Datasets

Comparison of the reviewed methods

Conclusion.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-031-89560-6

OCLC:

1524421710