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Authors:
Ali Boyali
Naohisa Hashimoto
Osamu Matsumato
Keywords: Robotic Wheel-chair control, Gesture and Posture Recognition, Compressed Sensing, Block Sparse Recovery, Sparse Representation based Classification.
Abstract:
In this study, a gesture and posture recognition method which is based on the Block Sparse, Sparse Representative Classification, and its use for a robotic wheel-chair control are explained. A Leap Motion sensor is used to capture the postures of the left hand. There are five postures mapped to the control commands of the power wheel-chair. These commands can be expanded as the posture recognition commands can deal with high number of classes. The MATLAB functions used in the computations are compiled into .NET programing environment. We tested the hand posture control in a hall where are occupied by tables and chairs. The navigation experiments were successful.
Pages: 20 to 25
Copyright: Copyright (c) IARIA, 2014
Publication date: July 20, 2014
Published in: conference
ISSN: 2308-3727
ISBN: 978-1-61208-363-6
Location: Paris, France
Dates: from July 20, 2014 to July 24, 2014