Full-body gestures and movements recognition: user descriptive and unsupervised learning approaches in GDL classifier

Tomasz Hachaj; Marek R. Ogiela

doi:10.1117/12.2061171

23 September 2014 Full-body gestures and movements recognition: user descriptive and unsupervised learning approaches in GDL classifier

Tomasz Hachaj, Marek R. Ogiela

Author Affiliations +

Proceedings Volume 9217, Applications of Digital Image Processing XXXVII; 921704 (2014) https://doi.org/10.1117/12.2061171
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

Gesture Description Language (GDL) is a classifier that enables syntactic description and real time recognition of full-body gestures and movements. Gestures are described in dedicated computer language named Gesture Description Language script (GDLs). In this paper we will introduce new GDLs formalisms that enable recognition of selected classes of movement trajectories. The second novelty is new unsupervised learning method with which it is possible to automatically generate GDLs descriptions. We have initially evaluated both proposed extensions of GDL and we have obtained very promising results. Both the novel methodology and evaluation results will be described in this paper.

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Tomasz Hachaj and Marek R. Ogiela "Full-body gestures and movements recognition: user descriptive and unsupervised learning approaches in GDL classifier", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921704 (23 September 2014); https://doi.org/10.1117/12.2061171

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