Custom cover image
Custom cover image

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

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Studies in Systems, Decision and Control ; 593Publisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Edition: 1st ed. 2025Description: 1 Online-Ressource(XIX, 96 p. 22 illus., 18 illus. in color.)ISBN:
  • 9783031895609
Subject(s): Additional physical formats: 9783031895593 | 9783031895616 | 9783031895623 | Erscheint auch als: 9783031895593 Druck-Ausgabe | Erscheint auch als: 9783031895616 Druck-Ausgabe | Erscheint auch als: 9783031895623 Druck-AusgabeDDC classification:
  • 006.37 23
DOI: DOI: 10.1007/978-3-031-89560-9Online resources: Summary: Introduction -- Background -- Research objectives and method -- Datasets -- Comparison of the reviewed methods -- Conclusion.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.PPN: PPN: 1927327326Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS
No physical items for this record
KIT – The Research University in the Helmholtz Association                         Home | Impressum | Datenschutz | Barrierefreiheit | KIT