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2017 | OriginalPaper | Chapter

9. A Novel Approach to Extract Hand Gesture Feature in Depth Images

Authors : Honghai Liu, Zhaojie Ju, Xiaofei Ji, Chee Seng Chan, Mehdi Khoury

Published in: Human Motion Sensing and Recognition

Publisher: Springer Berlin Heidelberg

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Abstract

This chapter proposes a novel approach to extract human hand gesture features in real-time from RGB-D images based on the earth mover’s distance and Lasso algorithms. Firstly, hand gestures with hand edge contour are segmented using a contour length information based de-noise method. A modified finger earth mover’s distance algorithm is then applied to locate the palm image and extract fingertip features. Lastly and more importantly, a Lasso algorithm is proposed to effectively and efficiently extract the fingertip feature from a hand contour curve. Experimental results are discussed to demonstrate the effectiveness of the proposed approach.

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previous chapter Human Hand Motion Analysis with Multisensory Information
next chapter Recognizing Constrained 3D Human Motion: An Inference Approach
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Metadata
Title
A Novel Approach to Extract Hand Gesture Feature in Depth Images
Authors
Honghai Liu
Zhaojie Ju
Xiaofei Ji
Chee Seng Chan
Mehdi Khoury
Copyright Year
2017
Publisher
Springer Berlin Heidelberg
Book
Human Motion Sensing and Recognition

Print ISBN: 978-3-662-53690-2

Electronic ISBN: 978-3-662-53692-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-662-53692-6_9

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