Robust hand gesture recognition from 3D data
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Date issued
2015
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Václav Skala - UNION Agency
Abstract
In this paper, we use the output of a 3D sensor (ex. Kinect from Microsoft) to capture depth images of humans
making a set of predefined hand gestures in various body poses. Conventional approaches using Kinect data have
been constrained by the limitation of the human detector middleware that requires close conformity to a standard
near erect, legs apart, hands apart pose for the subject. Our approach also permits clutter and possible motion
in the scene background, and to a limited extent, in the foreground as well. We make an important point in this
work to emphasize that the recognition performance is considerably improved by a choice of hand gestures that
accommodate the sensor’s specific limitations. These sensor limitations include low resolution in x and y as well
as z. Hand gestures have been chosen(designed) for easy detection by seeking to detect a fingers apart, fingertip
constellation with minimum computation. without, however compromising on issues of utility or ergonomy. It is
shown that these gestures can be recognised in real time irrespective of visible band illumination levels, background
motion, foreground clutter, user body pose, gesturing speeds and user distance. The last is of course limited by the
sensor’s own range limitations. Our main contributions are the selection and design of gestures suitable for limited
range, limited resolution 3D sensors and the novel method of depth slicing used to extract hand features from the
background. This obviates the need for preliminary human detection and enables easy detection and highly reliable
and fast (30 fps) gesture classification.
Description
Subject(s)
rozpoznávání gest rukou, kinetika, hloubková mapa, histogram, hloubkové krájení, konstelace otisků
Citation
WSCG '2015: short communications proceedings: The 23rd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2015 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech Republic8-12 June 2015, p. 159-166.