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.
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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.
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.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 116 pp. Englisch. Seller Inventory # 9783031895623
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Taschenbuch. Condition: Neu. Advances in Gait-Based Identification | A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques | Diogo R. M. Bastos (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | xix | Englisch | 2026 | Springer | EAN 9783031895623 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 135780616
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783031895623
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. 116 pp. Englisch. Seller Inventory # 9783031895623