Home // UBICOMM 2012, The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies // View article
Authors:
Myeong-Chun Lee
Sung-Bae Cho
Keywords: mobile interface; gesture recognition; hierarchical neural network; bidirectional recurrent neural network; long short-term memory
Abstract:
As the sensors embedded to a smartphone are proliferating, many application systems for context-aware services are actively investigated. This paper proposes a gesture recognition system with smartphones for better interface. It is important to maintain high accuracy even with the large number of gestures. To improve the accuracy, we adopt the recurrent neural network based on hierarchical BLSTM (Bidirectional Long Short-Term Memory). The first level BLSTMs are used to discriminate the gestures and non-gestures, and the second level BLSTMs classify the input into one of twenty gestures. Experiments with 24,850 sequence data consisting of 11,885 gesture sequences and 12,965 non-gesture sequences confirm the high performance of the proposed method over the competitive alternatives.
Pages: 138 to 141
Copyright: Copyright (c) IARIA, 2012
Publication date: September 23, 2012
Published in: conference
ISSN: 2308-4278
ISBN: 978-1-61208-236-3
Location: Barcelona, Spain
Dates: from September 23, 2012 to September 28, 2012