Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Aug 2018
Next issue: Nov 2018
Avg review time: 82 days


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

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


2,072,827 unique visits
Since November 1, 2009

Robots online now


SCImago Journal & Country Rank

SEARCH ENGINES - Google Pagerank


Anycast DNS Hosting

 Volume 18 (2018)
     »   Issue 3 / 2018
     »   Issue 2 / 2018
     »   Issue 1 / 2018
 Volume 17 (2017)
     »   Issue 4 / 2017
     »   Issue 3 / 2017
     »   Issue 2 / 2017
     »   Issue 1 / 2017
 Volume 16 (2016)
     »   Issue 4 / 2016
     »   Issue 3 / 2016
     »   Issue 2 / 2016
     »   Issue 1 / 2016
 Volume 15 (2015)
     »   Issue 4 / 2015
     »   Issue 3 / 2015
     »   Issue 2 / 2015
     »   Issue 1 / 2015
  View all issues  


Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


  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
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (752 KB) | Citation | Downloads: 564 | Views: 2,537

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

Quick view
Full text preview
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 31] [SCOPUS Times Cited 10]

[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.

[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.

[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 73]

[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 88]

[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] [SCOPUS Times Cited 3]

[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 3] [SCOPUS Times Cited 5]

References Weight

Web of Science® Citations for all references: 34 TCR
SCOPUS® Citations for all references: 184 TCR

Web of Science® Average Citations per reference: 2 ACR
SCOPUS® Average Citations per reference: 11 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 2018-10-21 10:22 in 57 seconds.

Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2018
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.

Website loading speed and performance optimization powered by: