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2015 | OriginalPaper | Chapter

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

Authors : Seongjo Lee, Sohyun Sim, Kyhyun Um, Young-Sik Jeong, Kyungeun Cho

Published in: Ubiquitous Computing Application and Wireless Sensor

Publisher: Springer Netherlands

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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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Literature
1.
go back to reference Kim YS, Park SY, Ok SY, Lee SH, Lee EJ (2012) Human gesture recognition technology based on user experience for multimedia contents control. J Korea Multimedia Soc 15(10):1196–1204CrossRef Kim YS, Park SY, Ok SY, Lee SH, Lee EJ (2012) Human gesture recognition technology based on user experience for multimedia contents control. J Korea Multimedia Soc 15(10):1196–1204CrossRef
2.
go back to reference Cho SY, Byun HR, Lee HK, Cha JH (2012) Arm gesture recognition for shooting games based on Kinect sensor. J KIISE Softw Appl 39(10):796–805 Cho SY, Byun HR, Lee HK, Cha JH (2012) Arm gesture recognition for shooting games based on Kinect sensor. J KIISE Softw Appl 39(10):796–805
3.
go back to reference Heo SK, Shin YS, Kim HS, Kim IC (2013) Design of an arm gesture recognition system using feature transformation and Hidden Markov models. KIPS Trans Softw Data Eng 2(10):723–730CrossRef Heo SK, Shin YS, Kim HS, Kim IC (2013) Design of an arm gesture recognition system using feature transformation and Hidden Markov models. KIPS Trans Softw Data Eng 2(10):723–730CrossRef
4.
go back to reference Sohn MK, Lee SH, Kim DJ, Kim B, Kim H (2013) 3D hand gesture recognition from one example. In: IEEE, 2013 IEEE international conference on consumer electronics (ICCE), pp 171–172 Sohn MK, Lee SH, Kim DJ, Kim B, Kim H (2013) 3D hand gesture recognition from one example. In: IEEE, 2013 IEEE international conference on consumer electronics (ICCE), pp 171–172
5.
go back to reference Biswas KK, Basu SK (2011) Gesture recognition using Microsoft Kinect®. In: IEEE, 2011 5th international conference on automation, robotics and applications (ICARA), pp 100–103 Biswas KK, Basu SK (2011) Gesture recognition using Microsoft Kinect®. In: IEEE, 2011 5th international conference on automation, robotics and applications (ICARA), pp 100–103
6.
go back to reference Wang Y, Yang C, Wu X, Xu S, Li H (2012) Kinect based dynamic hand gesture recognition algorithm research. In: IEEE, 2012 4th international conference on intelligent human-machine systems and cybernetics (IHMSC), vol 1, pp 274–279 Wang Y, Yang C, Wu X, Xu S, Li H (2012) Kinect based dynamic hand gesture recognition algorithm research. In: IEEE, 2012 4th international conference on intelligent human-machine systems and cybernetics (IHMSC), vol 1, pp 274–279
7.
go back to reference Park KS, Lee DH, Park YT (2013) Hand gesture recognition using depth information and visual image. J KIIT 11(7):57–65 Park KS, Lee DH, Park YT (2013) Hand gesture recognition using depth information and visual image. J KIIT 11(7):57–65
8.
go back to reference Lee KH, Choi JH (2004) Hand gesture sequence recognition using morphological chain code edge vector. J Korea Soc Comput Inf 9(4):85–91MathSciNet Lee KH, Choi JH (2004) Hand gesture sequence recognition using morphological chain code edge vector. J Korea Soc Comput Inf 9(4):85–91MathSciNet
Metadata
Title
Hand Gesture Recognition Using 8-Directional Vector Chains in Quantization Space
Authors
Seongjo Lee
Sohyun Sim
Kyhyun Um
Young-Sik Jeong
Kyungeun Cho
Copyright Year
2015
Publisher
Springer Netherlands
DOI
https://doi.org/10.1007/978-94-017-9618-7_31