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An implementation of an FPGA-based embedded gesture recognizer using a data glove

Published: 31 January 2008 Publication History

Abstract

A gesture recognizer based on a desktop PC, which uses existing wire/wireless communication modules, has several restrictions such as space limitations, movement limitations, and change in recognition capacity depending on the change in the background lighting conditions when obtaining a user's meaningful gesture data from images. This paper proposes an embedded gesture recognizer that uses a data glove in order to solve these problems. The proposed embedded FPGA (field-programmable gate array)-based gesture recognizer comprises an input module, a recognition module, and a display module. The input module receives the data that is transmitted from a data glove through a UART. The recognition module determines whether one set of data is accurate by performing data calculations with a checksum function after receiving the input data and comparing it to the header byte. This module also analyzes the data from 17 distinct gestures and constructs recognition models, and then it extracts the hand gesture data and compares it to the recognition models to see if the gestures match any of the 17 models. The recognition module then transmits the recognition result to the display module. The display module displays the recognition result on an LCD screen. A data glove manufactured by 5DT was used to obtain the gesture inputs. The FPGA was the XC3S1000FG676 (Xilinx Inc.) and it was designed using VHDL. The experimental results showed a 94% average recognition rate when using the FPGA-based embedded gesture recognizer and the data glove.

References

[1]
Balaniuk R, Laugier C. Haptic interfaces in generic virtual reality systems. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. 2000.
[2]
F. Bonfatti. G. Gadaa. P. Daniela Monari. Reucable software Design for Programmable Logic controllers. ACM SIGPANT Notices, vol.20, No.11, pp. 31--40, 1995.
[3]
Kallio, S. Kela, J. Mantyjarvi, J. Online gesture recognition system for mobile interaction. Systems, Man and Cybernetics, IEEE International Conference on, 2003
[4]
Geer, D. Will gesture recognition technology point the way?. Volume 37, Issue 10, Oct. 2004 Page(s):20--23
[5]
T. S Huang and V. I. Pavloic. Hand Gesture Modeling, Analysis, and Synthesis. Proc. of International Workshop on Automatic Face-and Gesture-Recognition, pp.73--79, Zurich, June 1995.
[6]
Xia Liu, Kikuo Fujimura. Hand Gesture Recognition using Depth Data. Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FGR' '04)
[7]
L. Bretzner, I. Laptev, and T. Lindeberg, Hand gesture recognition using multi-scale colour features, hierarchical models and particle filtering, Proc. of the 5th Intl. Conf. on Automatic Face and Gesture Recognition, May 2002, Washington D.C., 423--428.
[8]
Y. Zhu, G. Xu, and D. J. Kriegman, A real-time approach to the spotting, representation, and recognition of hand gestures for human-computer interaction, Computer Vision and Image Understanding 85(3), 189--208, 2002.
[9]
E. Polat, M. Yeasin, and R. Sharma, Robust tracking of human body parts for collaborative human computer interaction, Computer Vision and Image Understanding 89(1): 44--69, 2003.
[10]
K. Oka, Y. Sato, and H. Koike, Real-time tracking of multiple fingertips and gesture recognition for augmented desk interface systems, Proc. of the 5th Intl. Conf. on Automatic Face and Gesture recognition, May 2002, Washington D.C.
[11]
Kim, J.-H., et al.: An Implementation of KSSL Recognizer for HCI Based on Post Wearable PC and Wireless Networks KES 2006. LNCS (LNAI), vol. 4251 Part I, pp. 788--797. Springer-Verlag, Berlin Heidelberg New York (2006)
[12]
Dongsheng Shen, Lianwen Jin, and Xiaobin Ma. FPGA Implementation of Feature Extraction and Neural Network Classifier for Handwritten Digit Recognition. Lecture Notes in Computer Science, Springer Berlin / Heidelberg, Vol. 3173, pp. 988--995, 2004.
[13]
S. H. Jin, J. U. Cho, K. H. Kwo, J. W. Jeon. Image Processing : An FPGA Implementation of Parallel Hardware Architecture for the Real-time Window-based Image Processing. Journal of Korea Information Processing Society (KIPS), Vol.13, No.3, 2006
[14]
Stephen J. Melnikoff, Steven F. Quigley, Martin J. Russell. Speech Recognition on an FPGA Using Discrete and Continuous Hidden Markov Models. Lecture Notes in Computer Science, Springer Berlin / Heidelberg, Vol. 2438, pp. 89--114, 2002
[15]
Vargas, F. L. Fagundes, R. D. R. Junior, D. B. A FPGA-based Viterbi algorithm implementation for speech recognition systems. proceeding of IEEE International Conference ICASSP '01, Vol. 2, pp. 1217--1220, 2001.
[16]
S.-G.Kim.: Korean Standard Sign Language Tutor. 1st edn. Osung Publishing Company, Seoul (2000)
[17]
5DT Data Glove 5 Manual : http://www.5dt.com
[18]
Richard O. Duda, Peter E. Hart, David G. Stork.: Pattern Classification, 2nd, Wiley, New York (2001)
[19]
Dietrich Paulus and Joachim Hornegger.: Applied Pattern Recognition, 2nd, Vieweg (1998)

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cover image ACM Conferences
ICUIMC '08: Proceedings of the 2nd international conference on Ubiquitous information management and communication
January 2008
604 pages
ISBN:9781595939937
DOI:10.1145/1352793
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 31 January 2008

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Author Tags

  1. FPGA
  2. VHDL
  3. gesture recognition

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  • MIC, Korea

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Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

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  • (2021)A Weft Knit Data GloveIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2021.306817370(1-12)Online publication date: 2021
  • (2018)A Survey on FPGA Implementations in Embedded Augmented Reality Applications2018 6th Edition of International Conference on Wireless Networks & Embedded Systems (WECON)10.1109/WECON.2018.8782056(23-26)Online publication date: Nov-2018
  • (2016)Hardware-accelerated pose estimation for embedded systems using Vivado HLS2016 International Conference on ReConFigurable Computing and FPGAs (ReConFig)10.1109/ReConFig.2016.7857173(1-7)Online publication date: Nov-2016
  • (2014)An assistive interpreter tool using glove-based hand gesture recognition2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)10.1109/IHTC.2014.7147529(1-5)Online publication date: Jun-2014
  • (2014)Implementing a Sensor Fusion Algorithm for 3D Orientation Detection with Inertial/Magnetic SensorsInnovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering10.1007/978-3-319-06773-5_41(305-310)Online publication date: 16-Oct-2014
  • (2013)The impact of motion dimensionality and bit cardinality on the design of 3D gesture recognizersInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2012.11.00571:4(387-409)Online publication date: 1-Apr-2013
  • (2012)Small gestures go a long wayProceedings of the Designing Interactive Systems Conference10.1145/2317956.2318006(328-337)Online publication date: 11-Jun-2012
  • (2011)The Matrix OnlineThe Virtual Future10.1007/978-0-85729-904-8_2(15-33)Online publication date: 27-Jul-2011

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