A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition

Soodamani Ramalingam; Uma Maheswari Mariappan

doi:10.1109/CCST.2016.7815709

A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition

Soodamani Ramalingam, Uma Maheswari Mariappan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

This paper proposes a fuzzy interval valued multicriteria decision making (MCDM) technique that aggregates information from multi-modal feature sets during decision making in a 3D face recognition system. In this paper, an interval
valued fuzzy TOPSIS technique is applied to a 3D face recognition system that is benchmarked against a set of databases. Such a system is shown to be useful in decision making when the choice of alternatives of the feature sets is
combinatorial and complex.

Original language	English
Title of host publication	2016 IEEE International Carnahan Conference on Security Technology
Place of Publication	US
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	8
ISBN (Electronic)	978-1-5090-1072-1
ISBN (Print)	978-1-5090-1073-8
DOIs	https://doi.org/10.1109/CCST.2016.7815709
Publication status	Published - 16 Jan 2017
Event	IEEE International Carnahan Conference on Security Technology - US, Orlando, Florida, United States Duration: 24 Oct 2016 → 27 Oct 2016

Conference

Conference	IEEE International Carnahan Conference on Security Technology
Country/Territory	United States
City	Orlando, Florida
Period	24/10/16 → 27/10/16

Keywords

disparity maps
fuzzy interval MCDM
TOPSIS
3d FACE RECOGNITION
range data

Access to Document

10.1109/CCST.2016.7815709

Accepted ManuscriptAccepted author manuscript, 1.03 MBLicence: CC BY

Cite this

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title = "A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition",

abstract = "This paper proposes a fuzzy interval valued multicriteria decision making (MCDM) technique that aggregates information from multi-modal feature sets during decision making in a 3D face recognition system. In this paper, an intervalvalued fuzzy TOPSIS technique is applied to a 3D face recognition system that is benchmarked against a set of databases. Such a system is shown to be useful in decision making when the choice of alternatives of the feature sets iscombinatorial and complex.",

keywords = "disparity maps, fuzzy interval MCDM, TOPSIS, 3d FACE RECOGNITION, range data",

author = "Soodamani Ramalingam and Mariappan, {Uma Maheswari}",

note = "Soodamani, R & Vimal, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida. This is the Accepted Manuscript version. The Version of Record is available online at IEEE Explore, doi: https://doi.org/10.1109/CCST.2016.7815709. ; IEEE International Carnahan Conference on Security Technology ; Conference date: 24-10-2016 Through 27-10-2016",

year = "2017",

month = jan,

day = "16",

doi = "10.1109/CCST.2016.7815709",

language = "English",

isbn = "978-1-5090-1073-8",

booktitle = "2016 IEEE International Carnahan Conference on Security Technology",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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Ramalingam, S & Mariappan, UM 2017, A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition. in 2016 IEEE International Carnahan Conference on Security Technology., 978-1-5090-1072-1/16/$31.00 ©2016 IEEE, Institute of Electrical and Electronics Engineers (IEEE), US, IEEE International Carnahan Conference on Security Technology, Orlando, Florida, United States, 24/10/16. https://doi.org/10.1109/CCST.2016.7815709

A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition. / Ramalingam, Soodamani; Mariappan, Uma Maheswari.
2016 IEEE International Carnahan Conference on Security Technology. US: Institute of Electrical and Electronics Engineers (IEEE), 2017. 978-1-5090-1072-1/16/$31.00 ©2016 IEEE.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition

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AU - Mariappan, Uma Maheswari

N1 - Soodamani, R & Vimal, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida. This is the Accepted Manuscript version. The Version of Record is available online at IEEE Explore, doi: https://doi.org/10.1109/CCST.2016.7815709.

PY - 2017/1/16

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N2 - This paper proposes a fuzzy interval valued multicriteria decision making (MCDM) technique that aggregates information from multi-modal feature sets during decision making in a 3D face recognition system. In this paper, an intervalvalued fuzzy TOPSIS technique is applied to a 3D face recognition system that is benchmarked against a set of databases. Such a system is shown to be useful in decision making when the choice of alternatives of the feature sets iscombinatorial and complex.

AB - This paper proposes a fuzzy interval valued multicriteria decision making (MCDM) technique that aggregates information from multi-modal feature sets during decision making in a 3D face recognition system. In this paper, an intervalvalued fuzzy TOPSIS technique is applied to a 3D face recognition system that is benchmarked against a set of databases. Such a system is shown to be useful in decision making when the choice of alternatives of the feature sets iscombinatorial and complex.

KW - disparity maps

KW - fuzzy interval MCDM

KW - TOPSIS

KW - 3d FACE RECOGNITION

KW - range data

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DO - 10.1109/CCST.2016.7815709

M3 - Conference contribution

SN - 978-1-5090-1073-8

BT - 2016 IEEE International Carnahan Conference on Security Technology

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - US

T2 - IEEE International Carnahan Conference on Security Technology

Y2 - 24 October 2016 through 27 October 2016

ER -

A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition

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Keywords

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