Fundamentals of automated human gesture recognition using 3D integral imaging: a tutorial
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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INVESTIGACIONMetadata
Title
Fundamentals of automated human gesture recognition using 3D integral imaging: a tutorialAuthor (s)
Date
2020-12-31Publisher
Optical Society of AmericaISSN
1943-8206Bibliographic citation
Bahram Javidi, Filiberto Pla, José M. Sotoca, Xin Shen, Pedro Latorre-Carmona, Manuel Martínez-Corral, Rubén Fernández-Beltrán, and Gokul Krishnan, "Fundamentals of automated human gesture recognition using 3D integral imaging: a tutorial," Adv. Opt. Photon. 12, 1237-1299 (2020)Type
info:eu-repo/semantics/articlePublisher version
https://www.osapublishing.org/aop/fulltext.cfm?uri=aop-12-4-1237Version
info:eu-repo/semantics/publishedVersionAbstract
Automated human gesture recognition is receiving significant research interest, with applications ranging from novel acquisition techniques to algorithms, data processing, and classification methodologies. This tutorial ... [+]
Automated human gesture recognition is receiving significant research interest, with applications ranging from novel acquisition techniques to algorithms, data processing, and classification methodologies. This tutorial presents an overview of the fundamental components and basics of the current 3D optical image acquisition technologies for gesture recognition, including the most promising algorithms. Experimental results illustrate some examples of 3D integral imaging, which are compared to conventional 2D optical imaging. Examples of classifying human gestures under normal and degraded conditions, such as low illumination and the presence of partial occlusions, are provided. This tutorial is aimed at an audience who may or may not be familiar with gesture recognition approaches, current 3D optical image acquisition techniques, and classification algorithms and methodologies applied to human gesture recognition. [-]
Is part of
Advances in Optics and Photonics, 2020, vol. 12, no 4Funder Name
Generalitat Valenciana: PROMETEO/2019/048; Air Force Office of Scientific Research: FA9550-18-1-0338; Ministerio de Ciencia, Innovación y Universidades: RTI2018-099041-B-I00; Office of Naval Research: N000141712405,N000142012690,N000141712561
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© Copyright The Optical Society
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info:eu-repo/semantics/openAccess
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