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2017 | OriginalPaper | Chapter

Hand Gesture Recognition Using Interactive Image Segmentation Method

Authors : Disi Chen, Gongfa Li, Jianyi Kong, Guozhang Jiang, Ying Sun, Du Jiang, Zhaojie Ju

Published in: Intelligent Robotics and Applications

Publisher: Springer International Publishing

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Abstract

In this paper, a novel hand gesture recognition method using interactive image segmentation algorithm is proposed. We applied Gaussian mixture model to build the model of color image and the iteration of expectation maximum algorithm learnt the parameters. Then the graph model of color image is built. Finally, the segmentation is achieved by minimizing the energy of graph model according to min-cut/max-flow algorithm. Segmentation results were quantitatively tested and compared, by evaluate the region accuracy and boundary accuracy of segmentation results. To apply interactive image segmentation method into a fully automatic recognition framework, we applied human skin feature and depth information to generate the initial seeds. We also built a hand gesture database which contains ten kind of hand gestures for recognition test, proving that the segmentation of hand gesture images improved the recognition accuracy.

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previous chapter A Review of Gesture Recognition Based on Computer Vision
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Metadata
Title
Hand Gesture Recognition Using Interactive Image Segmentation Method
Authors
Disi Chen
Gongfa Li
Jianyi Kong
Guozhang Jiang
Ying Sun
Du Jiang
Zhaojie Ju
Copyright Year
2017
Book
Intelligent Robotics and Applications

Print ISBN: 978-3-319-65288-7

Electronic ISBN: 978-3-319-65289-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-65289-4_51

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