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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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2017-Jun-14
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.

2017-Apr-04
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2017-Feb-16
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.

2017-Jan-30
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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  4/2011 - 3

Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

RISTIC-DURRANT, D. See more information about RISTIC-DURRANT, D. on SCOPUS See more information about RISTIC-DURRANT, D. on IEEExplore See more information about RISTIC-DURRANT, D. on Web of Science, GRIGORESCU, S. M. See more information about  GRIGORESCU, S. M. on SCOPUS See more information about  GRIGORESCU, S. M. on SCOPUS See more information about GRIGORESCU, S. M. on Web of Science, GRASER, A. See more information about  GRASER, A. on SCOPUS See more information about  GRASER, A. on SCOPUS See more information about GRASER, A. on Web of Science, COJBASIC, Z. See more information about  COJBASIC, Z. on SCOPUS See more information about  COJBASIC, Z. on SCOPUS See more information about COJBASIC, Z. on Web of Science, NIKOLIC, V. See more information about NIKOLIC, V. on SCOPUS See more information about NIKOLIC, V. on SCOPUS See more information about NIKOLIC, V. on Web of Science
 
Click to see author's profile on 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 (574 KB) | Citation | Downloads: 1,053 | Views: 2,965

Author keywords
robust robot vision, feedback control in image processing, feature-based object recognition, neuro-fuzzy classification, assistive robot

References keywords
vision(8), systems(8), object(7), robots(6), robotics(6), graeser(6), system(5), robot(5), autonomous(5), robotic(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 15 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04003
Web of Science Accession Number: 000297764500003
SCOPUS ID: 84856594148

Abstract
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Full text preview
A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.


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

[1] D. Kim, R. Lovelett, A. Behal, "An empirical study with simulated adl tasks using vision-guided assistive robot arm", in Proc. of the IEEE 11th Int. Conf. on Rehabilitation Robotics ICORR, Japan, 2009.
[CrossRef] [SCOPUS Times Cited 14]


[2] D. Kragic, H. I. Christensen, "Advances in robot vision", Robotics and Autonomous Systems, vol. 52, pp. 1-3, 2005.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 18]


[3] S. Hussmann and T. Liepert, "Robot Vision System based on a 3D-TOF Camera", Instrumentation and Measurement Technology Conference-IMTC 2007, Warsaw, Poland, 2007.
[CrossRef]


[4] S. Gaechter, A. Harati and R. Siegwart, "Incremental Object Part Detection toward Object Classification in a Sequence of Noisy Range Images", in Proc. of IEEE International Conference on Robotics and Automation ICRA 2008, 2008.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 9]


[5] G. Mester, A. Rodic, Autonomous Locomotion of Humanoid Robots in Presence of Mobile and Immobile Obstacles, Towards Intelligent Engineering and Information Technology, Studies in Computational Intelligence, Volume 243, 2009.
[CrossRef] [SCOPUS Times Cited 1]


[6] T. Asfour, P. Azad, N. Vahrenkamp, K. Regenstein, A. Bierbaum, K. Welke, J. Schroder, R. Dillmann, Toward humanoid manipulation in human-centered environments, Robotics and Autonomous Systems, vol. 56, no. 1, pp. 54-65, 2008.
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 76]


[7] D. G. Lowe, "Distinctive image features from scale-invariant keypoints", Int. Journal of Computer Vision, vol. 60, no. 2, 2004.
[CrossRef] [Web of Science Times Cited 17783] [SCOPUS Times Cited 27207]


[8] D. Kragic, Bjoerman, H. Christensen, J.-O. Eklundh, "Vision for robotic object manipulation in domestic settings", Robotics and Autonomous Systems, vol. 52, pp. 85-100, 2005.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 59]


[9] M. Sridharan, P. Stone, "Structure-based color learning on a mobile robot under changing illumination", Autonomous Robots Journal, vol. 23, pp. 161-182, 2007.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 9]


[10] O. Ivlev, C. Martens, A. Graeser, "Rehabilitation robots FRIEND-I and FRIEND-II with the dexterous lightweight manipulator", Restoration of Wheeled Mobility in SCI Rehabilitation, vol. 17, pp. 111-123, 2005.

[11] O. Prenzel, C. Martens, M. Cyriacks, C. Wang, A. Graeser, "System controlled user interaction within the service robotic control architecture MASSiVE", Robotica, Special Issue, vol. 25, no. 2, 2007.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 13]


[12] D. Ojdanic, A. Graeser, "Improving the trajectory quality of a 7 DoF manipulator", in Proc. of the Robotik Conf., Munich, Germany, 2008.

[13] S. K. Vuppala, S. M. Grigorescu, D. Ristic-Durrant, A. Graeser, "Robust color object recognition for a service robotic task in the system FRIEND II", in Proc. of the IEEE 10th Int. Conf. on Rehabilitation Robotics ICORR, Noordwijk, Netherlands, 2007.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 9]


[14] P. Melin, O. Castillo, Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing, Springer-Verlag, 2005.

[15] P. Sanz, M. R., J. Sanchez, "Including efficient object recognition capabilities in online robots: From a statistical to a neural-network classifier", IEEE Trans. on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 35, no. 1, pp. 87-96, 2005.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 10]


[16] R. Jang, C-T. Sun, E. Mizutani, Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, 1997.

[17] E. Dogantekin, M. Yilmaz, A. Dogantekin, E. Avci, A. Sengur, "A robust technique based on invariant moments - ANFIS for recognition of human parasite eggs in microscopic images", Expert Systems with Applications, vol. 35, no. 3, pp. 728-738, 2008.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 27]


[18] R. Hartley, A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2004.
[CrossRef]


[19] S. K. Vuppala, A. Graeser, "An approach for tracking the 3d object pose using two object points", in Proc. of the Int. Conf. on Vision Systems ICVS, Santorini, Greece, 2008.
[CrossRef] [SCOPUS Record]


[20] D. Ristic, Feedback structures in image processing, Ph.D. thesis, Shaker Verlag, Germany, 2007.

[21] D. Ristic, A. Graser, "Performance measure as feedback variable in image processing", EURASIP Journal on Applied Signal Processing, vol. 2006, 2006.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 8]


[22] S. M. Grigorescu, D. Ristic-Durrant, A. Graeser, "ROVIS: Robust machine Vision for Service robotic system FRIEND", in Proc. of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, USA, October, 2009.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 13]


[23] M. Sridharan, "Bootstrap Learning and Visual Processing Management on Mobile Robots", Advances in Artificial Intelligence, vol. 2010, 2010.
[CrossRef]


[24] C. Suliman, C. Cruceru, F. Moldoveanu, "Kalman filter based tracking in an video surveillance system", Advances in Electrical and Computer Engineering, vol. 10, no. 2, pp. 30-34, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]


References Weight

Web of Science® Citations for all references: 17,950 TCR
SCOPUS® Citations for all references: 27,484 TCR

Web of Science® Average Citations per reference: 748 ACR
SCOPUS® Average Citations per reference: 1,145 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 2017-10-16 13:55 in 127 seconds.




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


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