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JCR Impact Factor: 0.700
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Current issue: Aug 2024
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PUBLISHER

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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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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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: 1,113 | Views: 4,506

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.


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Cited-By CrossRef

[1] 3D Hand Gesture Recognition using the Hough Transform, OPRISESCU, S., BARTH, E., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.03012
[CrossRef] [Full text]

[2] 3D Depth Information Based 2D Low-Complexity Hand Posture and Gesture Recognition Design for Human Computer Interactions, Chiang, Ti, Fan, Chih-Peng, 2018 3rd International Conference on Computer and Communication Systems (ICCCS), ISBN 978-1-5386-6350-9, 2018.
Digital Object Identifier: 10.1109/CCOMS.2018.8463327
[CrossRef]

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


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