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Internal Generative Mechanism Based Otsu Multilevel Thresholding Segmentation for Medical Brain Images Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Implementation of Human Action Recognition System Using Multiple Kinect Sensors

Authors : Beom Kwon, Doyoung Kim, Junghwan Kim, Inwoong Lee, Jongyoo Kim, Heeseok Oh, Haksub Kim, Sanghoon Lee

Published in: Advances in Multimedia Information Processing -- PCM 2015

Publisher: Springer International Publishing

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Abstract

Human action recognition is an important research topic that has many potential applications such as video surveillance, human-computer interaction and virtual reality combat training. However, many researches of human action recognition have been performed in single camera system, and has low performance due to vulnerability to partial occlusion. In this paper, we propose a human action recognition system using multiple Kinect sensors to overcome the limitation of conventional single camera based human action recognition system. To test feasibility of the proposed system, we use the snapshot and temporal features which are extracted from three-dimensional (3D) skeleton data sequences, and apply the support vector machine (SVM) for classification of human action. The experiment results demonstrate the feasibility of the proposed system.

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Metadata
Title
Implementation of Human Action Recognition System Using Multiple Kinect Sensors
Authors
Beom Kwon
Doyoung Kim
Junghwan Kim
Inwoong Lee
Jongyoo Kim
Heeseok Oh
Haksub Kim
Sanghoon Lee
Copyright Year
2015
Book
Advances in Multimedia Information Processing -- PCM 2015

Print ISBN: 978-3-319-24074-9

Electronic ISBN: 978-3-319-24075-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-24075-6_32