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JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 2017
Avg review time: 95 days


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: 644266260
doi: 10.4316/AECE


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2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

2015-Dec-04
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2015-Jun-10
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2015-Feb-09
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  3/2015 - 6

Automatic Assistant for Better Mobility and Improved Cognition of Partially Sighted Persons

TAPU, R. See more information about TAPU, R. on SCOPUS See more information about TAPU, R. on IEEExplore See more information about TAPU, R. on Web of Science, MOCANU, B. See more information about  MOCANU, B. on SCOPUS See more information about  MOCANU, B. on SCOPUS See more information about MOCANU, B. on Web of Science, ZAHARIA, T. See more information about ZAHARIA, T. on SCOPUS See more information about ZAHARIA, T. on SCOPUS See more information about ZAHARIA, T. on Web of Science
 
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Download PDF pdficon (1,707 KB) | Citation | Downloads: 194 | Views: 789

Author keywords
visual impaired navigation assistant, obstacle detection and classification, audio feedback, smartphone device

References keywords
visually(11), vision(11), impaired(10), system(5), detection(5), blind(5), visual(4), obstacle(4), navigation(4)
No common words between the references section and the paper title.

About this article
Date of Publication: 2015-08-31
Volume 15, Issue 3, Year 2015, On page(s): 45 - 52
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.03006
Web of Science Accession Number: 000360171500006
SCOPUS ID: 84940735074

Abstract
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In these paper we introduce a novel computer vision assistant for autonomous navigation of partially sighted people. We begin by detecting any type of static and dynamic obstacle present in the scene. Then, we introduce an adapted version of HOG (Histogram of Oriented Gradients) descriptor incorporated into the BoVW (Bag of Visual Words) retrieval framework and demonstrate how this combination can be used for obstacle classification. The design is completed with an acoustic feedback that alert user of potential hazards. The audio bone conduction is employed to allow the visually impaired to hear other sounds from the environment. At the hardware level, the system is totally integrated on a smartphone which makes it easy to wear, non-invasive and low-cost.


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

[1] D. Pascolini, S. P. Mariotti, "Global data on visual impairments 2010," World Health Organization, Geneva, 2012.

[2] B. B. Blasch, W. R. Wiener, and R. L. Welsh, "Foundations of Orientation and Mobility", 2nd New York: American Foundation for the Blind AFB Press, pp. 42-55, 1997.

[3] C. Shah, M. Bouzit, M. Youssef, and L. Vasquez, "Evaluation of RU-Netra Tactile Feedback Navigation System for the Visually Impaired," International Workshop on Virtual Rehabilitation, pp. 72-77, 2006.
[CrossRef]


[4] R. G. Golledge, J. R. Marston, and C. M. Costanzo, "Attitudes of visually impaired persons towards the use of public transportation," Journal of Visually Impairment Blindness, vol. 90, pp. 446-459, 1997.

[5] A. Rodriguez, J. J. Yebes, P. F. Alcantarilla, L. M. Bergasa, J. Almazan, and A. Cela, "Assisting the visually impaired: obstacle detection and warning system by acoustic feedback," Sensors, vol. 12, pp. 17476-17496, 2012.
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 34]


[6] D. Dakopoulos, N. G. Bourbakis, "Wearable obstacle avoidance electronic travel aids for blind: a survey," IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol.40, no.1, pp.25-35, Jan. 2010.
[CrossRef] [Web of Science Times Cited 91] [SCOPUS Times Cited 157]


[7] J. A. Hesch, S. I. Roumeliotis, "Design and analysis of a portable indoor localization aid for the visually impaired," Journal of Robotics Research, pp. 1400-1415, 2010.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 24]


[8] J. M. Saez, F. Escolano, and A. Peñalver, "First steps towards stereo based 6DOF SLAM for the visually impaired," IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, pp.23-23, June 2005.
[CrossRef]


[9] V. Pradeep, G. Medioni, J. Weiland, "Robot Vision for the Visually Impaired," IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.15-22, June 2010.
[CrossRef] [SCOPUS Times Cited 34]


[10] J. M. Saez, F. Escolano, "Stereo-Based Aerial Obstacle Detection for the Visually Impaired", In ECCV workshop. on Computer Vision Applications for the Visually Impaired, France 2008.

[11] J. M. Loomis, R. L. Klatzky, N. A. Giudice, "Sensory substitution of vision: importance of perceptual and cognitive processing", in Assistive Technology for Blindness and Low Vision, Eds. Boca Raton, pp. 161-192, 2013.

[12] P. B. L. Meijer, "An experimental system for auditory image representations", IEEE Trans. Biomedical Engineering, vol. 39(2), pp. 112-121, 1992.
[CrossRef] [Web of Science Times Cited 230] [SCOPUS Times Cited 357]


[13] J. L. Gonzalez-Mora, A. Rodriguez-Hernandez, L. F. Rodriguez-Ramos, L. Diaz-Saco, N. Sosa, "Development of a new space perception system for blind people, based on the creation of a virtual acoustic space", Lecture Notes in Computer Science Engineering Applications of Bio-Inspired Artificial Neural Networks, pp. 321-330, 1999.
[CrossRef] [SCOPUS Times Cited 15]


[14] S. Meers and K. Ward, "A substitute vision system for providing 3D perception and GPS navigation via electro-tactile stimulation," 1st Int. Conf. Sens. Technol., New Zealand, Nov. pp. 21-23, 2005.

[15] L. A. Johnson and C. M. Higgins, "A navigation aid for the blind using tactile-visual sensory substitution," in Proc. 28th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., pp. 6298-6292, 2006.
[CrossRef] [SCOPUS Times Cited 22]


[16] D. Dakopoulos and N. Bourbakis, "Preserving visual information in low resolution images during navigation for visually impaired," Proceedings of the 1st International Conference on PErvasive Technologies Related to Assistive Environments, Athens, Greece, pp. 1-6, 2008.
[CrossRef] [SCOPUS Record]


[17] A. Khan, F. Moideen, J. Lopez, W. L. Khoo, Z. Zhu, "KinDetect: Kinect detecting objects", in Computer Helping people with special needs, vol. LNCS7382, pp. 588-595, 2012.

[18] E. Peng, P. Peursum, L. Li, S. Venkatesh, "A smartphone-based obstacle sensor for the visually impaired", Lecture Notes in Computer Science, Ubiquitous Intelligence and Computing, pp. 590-604, 2010.
[CrossRef] [SCOPUS Times Cited 11]


[19] R. Manduchi, "Mobile vision as assistive technology for the blind: An experimental study", Proceedings of the 13th International Conference on Computers Helping People with Special Needs, volume 2, pp. 9-16, Austria, 2012.
[CrossRef] [SCOPUS Times Cited 5]


[20] R. Tapu, T. Zaharia, "Salient object detection based on spatiotemporal attention models," IEEE International Conference on Consumer Electronics (ICCE), pp.39-42, Jan. 2013.
[CrossRef] [SCOPUS Times Cited 2]


[21] N. Dalal, B. Triggs, "Histograms of oriented gradients for human detection", IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.1, pp.886-893, June 2005.
[CrossRef] [SCOPUS Times Cited 7469]


[22] N. Dalal, B. Triggs, "Object detection using histograms of oriented gradients", in European Conference on Computer Vision, vol. 1, pp 886-893, 2006.

[23] G. Csurka, C. R. Dance, L. Fan, J. Willamowski, C. Bray, "Visual categorization with bags of keypoints," In Workshop on Statistical Learning in Computer Vision, ECCV, pp. 1-22, 2004.

[24] S. Tong, E. Chang, "Support Vector Machine Active Learning for Image Retrieval," Proceedings of the Ninth ACM International Conference on Multimedia., pp. 107-118, 2001.
[CrossRef]




References Weight

Web of Science® Citations for all references: 366 TCR
SCOPUS® Citations for all references: 8,130 TCR

Web of Science® Average Citations per reference: 15 ACR
SCOPUS® Average Citations per reference: 325 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 2016-12-02 13:54 in 95 seconds.




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


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