Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery

AUTHORS

Ranbeer Tyagi,Deptt. of E&TC, MITS, Gwalior & Uttarakhand Technical University, Dehradun, India
Geetam Singh Tomar,Deptt. of Electronics & Communication, THDC-IHET Tehri Garhwal Uttarakhand, India
Laxmi Shrivastava,Deptt. of Electronics Engineering, MITS, Gwalior (M.P.) India

ABSTRACT

This paper represents the Id Quality of un-constrained face inside an unconstrained environment. It provides capabilities like discrepancy, illumination, and expression difference techniques. It might be useful for both retrieve image (Face) and identification (Recognition). At present plenty of way of top view face recognition can be found. In last few years, for Computer vision, numerous face recognition techniques have been organized. But, actual-world face detection demands a difficult works. The curiosity about unconstrained helpful face recognition keeps growing utilizing the detonation of online press for instance community methods, and video surveillance recording wherever experience analysis is of great importance. In this analysis, it is appeared to handle status inside the scenario of chart assumption. We're in a position to determine a magical experience employing a Varied Technique. This study lights out the choices suggested for unconstrained face recognition quality area and suggesting the solution to be utilized by Reference Face Based Technique (From Gallery Image) centered face recognition. RFG recognition is used in grouping with DCT locality sensitive hashing for efficient recovery to guarantee scalability. Objective of this research is Reference Face Based Technique focused on unconstrained face recognition to enhance the demonstration quality. The Simulation of proposed techniques will be completed through the use of MATLAB.

 

KEYWORDS

Reference Face Based Technique, Unconstrained Face, DCT, RFG, Guide Block

REFERENCES

[1]     Ian T. Young Jan, J. Gerbrands, Lucas J. van Vliet, “Fundamental of Image Processing”, (1995).
[2]     Doo Hyun Choi, Ick Hoon Jang, Mi Hye Kim, Nam Chul Kim, “Color image enhancement using single-scale retinex based on an improved image formation model”, 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, August pp.25-29, (2008).
[3]     Leila Fallah Araghi, Mohammad Reza Arvan, “An Implementation Image Edge and Feature Detection Using Neural Network” Proceedings of the International Multi Conference of Engineers and Computer Scientists ,Vol I, March 18-20, (2009).
[4]     Abhijith Punnappurath, Ambasamudram Narayanan Rajagopalan,Sima Taheri, Rama Chellappa, “Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose” IEEE Transactions on image processing, vol. 24, no. 7, july (2015).DOI: 10.1109/TIP.2015.2412379(CrossRef)(Google Scholar)
[5]     Rafel C. Gonzalez, Richard E. Woods, “Digital image processing”, third edition, (2008). DOI: 10.1109/IEMDC.2013.6556306(CrossRef)(Google Scholar)
[6]     Mehran Kafai, Le An and Bir Bhanu “Reference Face Graph for Face Recognition”, IEEE Transactions on information forensics and security, Vol.9, No.12, pp.2132-2143, 19 Sept. (2014). DOI: 10.1109/TIFS.2014.2359548(CrossRef)(Google Scholar)
[7]     Tyagi, R., Tomar, G. S., Shirvastava, “Unconstrained face recognition Quality: A review”, International Journal of Signal Processing, Image Processing and Pattern Recognition, (2016), Vol.9, No.11, pp. 199-210
[8]     Tyagi, R., Tomar, G. S., Baik, N. “A Survey of Unconstrained face recognition algorithms and its application” International Journal of Security and Its Application, (2016), Vol.10, No.12, pp. 369-376
[9]     "Face Recognition Applications". Animetrics. (2008)
[10]  "Facial Recognition: Who's Tracking You in Public?". Consumer Reports. (2016).
[11]  Jocelyn C. , Adams Kristen C. Allen , Tim Miller, Nathan D. Kalka and Anil K. Jain, “Grouper: Optimizing Crowdsourced Face Annotations”  IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pp. 163-170, June (2016).DOI: 10.1109/CVPRW.2016.27(CrossRef)(Google Scholar)
[12]  Lacey Best-Rowden, Hu Han, Charles Otto, Brendan Klare, and Anil K. Jain, “Unconstrained Face Recognition: Identifying a Person of Interest from a Media Collection, IEEE Transactions on Information Forensics and Security, vol.-9, Issue-12, pp. 2144-2157, Dec.-(2014).DOI: 10.1109/TIFS.2014.2359577(CrossRef)(Google Scholar)
[13]  Tyagi, R., Tomar, G. S.: ‘Tranformation of Image from Color to Gray Scale Using contrast among DPCM and LMS Method’ Internation Journal of Signal Processing,Image Processing and Pattern Recognition, (2016), 9, (8), pp. 11-24
[14]  Tyagi, R., Tomar, G. S.: ‘Unfamiliar Sides, video, image enhancement in face recognition’ International Journal of Hybrid Information Technology, (2016), Vol.9, No.11, pp. 255-266
[15]  C. Ding and D. Tao, “A Comprehensive Survey on Pose-Invariant Face Recognition” ACM Transactions on Intelligent Systems and Technology (TIST), Vol.7, No.3, pp.1-40, April (2016). DOI: 10.1145/2845089(CrossRef)(Google Scholar)
[16]  Mara Olekalns and Daniel Druckman, “With Feeling: How Emotions Shape Negotiation” in the Negotiation Journal, Volume 30, Number 6, October (2014). DOI: 10.1007/978-94-017-9963-8_2(CrossRef)(Google Scholar)
[17]  A. Punnappurath, A. N. Rajagopalan, S. Taheri, R. Chellappa, “Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose” IEEE Transactions on image processing, vol. 24, no. 7, july (2015). DOI: 10.1109/TIP.2015.2412379(CrossRef)(Google Scholar)
[18]  P. Vageeswaran, K. Mitra, and R. Chellappa, “Blur and illumination robust face recognition via set-theoretic characterization,” IEEE Trans. Image Process., Vol. 22, No. 4, pp. 1362-1372, Apr. (2013).DOI: 10.1109/TIP.2012.2228498(CrossRef)(Google Scholar)
[19]  S. Sengupta, J. C. Chen, C. Castillo, V. M. Patel, R. Chellappa, and D. W. Jacobs, “Frontal to Profile Face Verification in the Wild” IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1-9, March (2016). DOI: 10.1109/WACV.2016.7477558(CrossRef)(Google Scholar)
[20]  Jun-Cheng Chen, V. M. Patel, and R. Chellappa, “Unconstrained Face Verification using Deep CNN Features” IEEE Winter Conference on Applications of Computer Vision (WACV), pp.-1-9, March-(2016).DOI: 10.1109/WACV.2016.7477557(CrossRef)(Google Scholar)
[21]  S. Liao, Z. Lei, D. Yi, and S. Z. Li, “A Benchmark Study of Large-scale Unconstrained Face Recognition” IEEE International Joint Conference on Biometrics (IJCB), pp.1-8, sep.-29-oct.-2-(2014).DOI: 10.1109/BTAS.2014.6996301(CrossRef)(Google Scholar)
[22]  Thi Thanh Thuy Phama, Thi-Lan Lea,  Hai Vua, Trung Kien Daoa and Van Toi Nguyenc, “Fully-automated person re-identification in multi-camera surveillance system with a robust kernel descriptor and effective shadow removal method” Image and Vision Computing, Publisher-Elsevier, Vol.59, pp.44-62, March (2017).DOI: 10.1016/j.imavis.2016.10.010(CrossRef)(Google Scholar)
[23]  Hardeep Kaur and Amandeep Kaur, “Illumination Invariant Face Recognition” International Journal of Computer Applications (0975 – 8887), Vol.64, No.21, pp.23-27, Feb.-(2013).
[24]  C.Indhumathi, “Unconstrained Face Recognition From Blurred and Illumination with Pose Variant Face Image Using SVM” International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol.2, Special Issue 1, pp. 2564-2567, March (2014).
[25]  A.Devi and A.Marimuthu, “Image Processing Techniques in Face Recognition” International Journal of Computer Trends and Technology, Vol.4, No.2, pp.59-62, (2013).
[26]  [Keyurkumar Patel, Hu Han and Anil K. Jain, “Secure Face Unlock: Spoof Detection on Smartphones” IEEE transactions on information forensics and security, Vol.11, No.10, October (2016). DOI: 10.1109/TIFS.2016.2578288(CrossRef)(Google Scholar)
[27]  D. Wang, C. Otto and A. K. Jain, "Face Search at Scale", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.39, No.6, pp.1122-1136, June (2017). DOI: 10.1109/tpami.2016.2582166(CrossRef)(Google Scholar)

CITATION

  • APA:
    Tyagi,R.& Tomar,G.S.& Shrivastava,L.(2019). Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery. International Journal of Computer Graphics, 10(1), 1-16. http://dx.doi.org/10.21742/IJCG.2019.10.1.01
  • Harvard:
    Tyagi,R.and Tomar,G.S.and Shrivastava,L.(2019). "Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery". International Journal of Computer Graphics, 10(1), pp.1-16. doi:http://dx.doi.org/10.21742/IJCG.2019.10.1.01
  • IEEE:
    [1]R.Tyagiand G.S.Tomarand L.Shrivastava, "Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery". International Journal of Computer Graphics, vol.10, no.1, pp.1-16, Nov. 2019
  • MLA:
    Tyagi Ranbeerand Tomar Geetam Singhand Shrivastava Laxmi. "Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery". International Journal of Computer Graphics, vol.10, no.1, Nov. 2019, pp.1-16, doi:http://dx.doi.org/10.21742/IJCG.2019.10.1.01

ISSUE INFO

  • Volume 10, No. 1, 2019
  • ISSN(p):2093-9663
  • ISSN(o):2383-7284
  • Published:Nov. 2019

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