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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2012 - 13

An Efficient Solution for Hand Gesture Recognition from Video Sequence

PRODAN, R.-C. See more information about PRODAN, R.-C. on SCOPUS See more information about PRODAN, R.-C. on IEEExplore See more information about PRODAN, R.-C. on Web of Science, PENTIUC, S.-G. See more information about  PENTIUC, S.-G. on SCOPUS See more information about  PENTIUC, S.-G. on SCOPUS See more information about PENTIUC, S.-G. on Web of Science, VATAVU, R.-D. See more information about VATAVU, R.-D. on SCOPUS See more information about VATAVU, R.-D. on SCOPUS See more information about VATAVU, R.-D. on Web of Science
 
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Download PDF pdficon (752 KB) | Citation | Downloads: 1,040 | Views: 4,249

Author keywords
human robot interaction, computer vision, robotic arm, gesture recognition, image processing

References keywords
recognition(7), robot(6), gesture(6), vatavu(4), processing(4), interaction(4), image(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-08-31
Volume 12, Issue 3, Year 2012, On page(s): 85 - 88
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.03013
Web of Science Accession Number: 000308290500013
SCOPUS ID: 84865856673

Abstract
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The paper describes a system of hand gesture recognition by image processing for human robot interaction. The recognition and interpretation of the hand postures acquired through a video camera allow the control of the robotic arm activity: motion - translation and rotation in 3D - and tightening/releasing the clamp. A gesture dictionary was defined and heuristic algorithms for recognition were developed and tested. The system can be used for academic and industrial purposes, especially for those activities where the movements of the robotic arm were not previously scheduled, for training the robot easier than using a remote control. Besides the gesture dictionary, the novelty of the paper consists in a new technique for detecting the relative positions of the fingers in order to recognize the various hand postures, and in the achievement of a robust system for controlling robots by postures of the hands.


References | Cited By  «-- Click to see who has cited this paper

[1] Andrew D. Wilson, "Robust Vision-Based Detection of Pinching for One and Two-Handed Gesture Input", In Proceedings of ACM UIST '06, pp. 255-258, 2006.
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 14]


[2] S.G. Pentiuc, R.D. Vatavu, R. Prodan, T.I. Cerlinca, "Mathematical Model for a Robot Arm Control System", Advances in Electrical and Computer Engineering, vol. 5(12), no. 1(23), pp. 91-95, 2005

[3] Park, Hye Sun and Kim, Eun Yi and Jang, Sang Su and Park, Se Hyun and Park, Min Ho and Kim, Hang Joon, "HMM-Based Gesture Recognition for Robot Control", Pattern Recognition And Image Analysis, vol. 3522, pp. 695-716, 2005.
[CrossRef] [SCOPUS Times Cited 29]


[4] Seong-Whan Lee, "Automatic gesture recognition for intelligent human-robot interaction, 7th International Conference on Automatic Face and Gesture Recognition", FGR 2006, pp. 645-650, 2006

[5] Radu-Daniel Vatavu, "Interfaces That Should Feel Right: Natural Interaction with Multimedia Information", Recent Advances in Multimedia Signal Processing and Communications, Springer Studies in Computational Intelligence - Springer Berlin / Heidelberg, vol. 231, pp. 145-170, 2009.
[CrossRef] [SCOPUS Times Cited 5]


[6] Radu-Daniel Vatavu, Stefan-Gheorghe Pentiuc, "Interactive Coffee Tables: Interfacing TV within an Intuitive, Fun and Shared Experience", EuroITV 2008, pp. 183-187, 2008

[7] Regina Bernhaupt, Marianna Obrist, Astrid Weiss, Elke Beck, and Manfred Tscheligi, "Trends in the living room and beyond: results from ethnographic studies using creative and playful probing". Comput. Entertain (CIE). vol. 6, no. 1, article no. 5, 2008

[8] R. C. Gonzalez and R. E. Woods, "Digital Image Processing", Prentice-Hall, 2nd edition, 2002.

[9] William K. Pratt, "Digital Image Processing: PIKS Scientific Inside", 4th Ed., Wiley-Interscience, 2007.

[10] J. LaViola, "A survey of hand posture and gesture recognition techniques and technology", Technical Report CS-99-11, Department of Computer Science, Brown University, Providence RI, 1999.

[11] Mike Wu, Ravin Balakrishnan. "Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays". The 16-th Annual ACM Symposium on User interface Software and Technology, New York, pp. 193-202, 2003.
[CrossRef] [SCOPUS Times Cited 333]


[12] R.D. Vatavu, S.G. Pentiuc, C. Chaillou, L. Grisoni, Samuel Degrande, "Visual Recognition of Hand Postures for Interacting with Virtual Environments", Advances in Electrical and Computer Engineering, vol. 6 (13), no. 2(26), pp. 55-58, 2006

[13] Kemp, C. C., Anderson, C. D., Nguyen, H., Trevor, A. J., Xu, Z., "A Point-and-Click Interface for the Real World: Laser Designation of Objects for Mobile Manipulation". In 3rd ACM/IEEE International Conference on Human-Robot Interaction, pp. 241-248, 2008
[CrossRef] [SCOPUS Times Cited 108]


[14] Sakamoto, D., Honda, K., Inami, M., Igarashi, T., "Sketch and Run, A Stroke-based Interface for Home Robots", In 27th International Conference on Human Factors in Computing Systems, pp. 197-200, 2009

[15] Malima, A., Ozgur, E., Cetin, M., "A Fast Algorithm for Vision-Based Hand Gesture Recognition for Robot Control", in Proceedings of IEEE 14-th Conf. on Signal Processing and Communications Applications, pp. 1-4, 2006.
[CrossRef] [SCOPUS Times Cited 142]


[16] E. Ganea, D. D. Burdescu, M. Brezovan, "New Method to Detect Salient Objects in Image Segmentation using Hypergraph Structure," Advances in Electrical and Computer Engineering, vol. 11, no. 4, pp. 111-116, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 5]


[17] D. Ristic-Durrant, S. M. Grigorescu, A. Graser, Z. Cojbasic, V. Nikolic, "Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND," Advances in Electrical and Computer Engineering, vol. 11, no. 4, pp. 15-22, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 13]


References Weight

Web of Science® Citations for all references: 53 TCR
SCOPUS® Citations for all references: 649 TCR

Web of Science® Average Citations per reference: 3 ACR
SCOPUS® Average Citations per reference: 38 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-05-22 07:59 in 56 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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