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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.
Published by: Springer
Publication Date: 2025-05-31
Format: Hardcover
ISBN-13: 9783031895593
DOI: 10.1007/978-3-031-89560-9
Dimensions: 235cm x155cm
Pages: 96