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Hand Gesture Recognition Using 8-Directional Vector Chains in Quantization Space

Authors
Lee, SeongjoSim, SohyunUm, KyhyunJeong, Young-SikCho, Kyungeun
Issue Date
2015
Publisher
SPRINGER
Keywords
Hand gesture recognition; Kinect sensor; Hidden Markov model; Multimedia content
Citation
UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR, v.331, pp 333 - 340
Pages
8
Indexed
SCOPUS
Journal Title
UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR
Volume
331
Start Page
333
End Page
340
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/25361
DOI
10.1007/978-94-017-9618-7_31
ISSN
1876-1100
1876-1119
Abstract
This paper proposes a hand gesture recognition technique that allows users to enjoy uninterrupted interaction with a variety of multimedia applications. Hand gestures are recognized using joint information acquired from a Kinect sensor, and the recognized gestures are applied to multimedia content. To this end, hand gestures are quantized in the grid space, expressed using an 8-directional vector chain, and finally recognized on the basis of a hidden Markov model. To assess the proposed approach, we define the hand gestures used in the "Smart Interior" multimedia application, and collect a dataset of gestures using the Kinect. Our experiments demonstrate a high recognition ratio of between 90 and 100 %. Furthermore, the experiments identify the possibility of applying this approach to a variety of multimedia content by verifying its superior operation in actual applications.
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