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Immediately-available Input Method Using One-handed Motion in Arbitrary Postures
Author(s) -
Moyuru Yamada,
Shan Jiang,
Katsushi Sakai,
Yuichi Murase,
Keiju Okabayashi
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.11.009
Subject(s) - computer science , motion (physics) , artificial intelligence , computer vision
This paper presents an input method, which enables the user to immediately interact with services using one-handed motion in arbitrary postures. This method is mainly targeted at workers who work with dirty hands or hold tools in their hands. To allow the workers to control applications as intended without handheld devices while they operate their hand work in various postures, we propose intentional segmentation, motion trajectory estimation of the wrist, and three types of inputs using wrist motions. The segmentation controller enables users to intentionally distinguish input motion from normal hand work by the wrist state without limiting the range of upper limb motion and immediately start performing the input motion. We estimate the motion trajectories of the wrist in the input segment using inertial sensors attached to the wrist, and recognize gestures from the trajectories without training data sets. The users can control various applications by three types of inputs: continuous inputs linked to the wrist motions, discrete inputs by gestures, and specific inputs generated from these. We also developed a wristwatch-like wearable device to evaluate the effectiveness of the proposed method. Through the two experimental evaluations, we showed the ease of learning the proposed method and achieved a mean recognition rate of 94.3% in various postures for six defined gestures

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