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RESEARCH PRODUCT
Fundamentals of automated human gesture recognition using 3D integral imaging: a tutorial
Bahram JavidiRuben Fernandez-beltranXin ShenManuel Martínez-corralFiliberto PlaPedro Latorre CarmonaGokul KrishnanJosé Martínez Sotocasubject
Integral imagingData processingbusiness.industryComputer scienceImage qualityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONautomated human gesture recognitionRangingImage processing02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesAtomic and Molecular Physics and Optics010309 opticsoptical imagingStatistical classification3D integral imagingGesture recognition0103 physical sciencesComputer visionArtificial intelligence0210 nano-technologybusinessGesturedescription
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.
year | journal | country | edition | language |
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2020-12-14 | Advances in Optics and Photonics |