Face Detection and Tagging Using Deep Learning

Jinesh Mehta, Eshaan Ramnani, Sanjay Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

With the social media boom in today's world, we see people constantly uploading photos of themselves along with their friends and family on various social media platforms such as Facebook, Instagram, Twitter, Google+, etc. What if they want to see all the photos in a categorized form such as photos with a particular person. In this paper, we extend the concept of Multiview Face Detection using Convolution Neural Networks (CNN) used by Farfade et al. by providing a tagging system for the detected faces. For the face detection, we use Deep Dense Face Detector, which uses a single model based on deep convolutional neural networks. All the detected faces are recognized using Local Binary Patterns Histograms (LBPH) method. Precision, recall, and F-measure are the parameters used to measure the performance of the algorithm. An accuracy of 85% is achieved for tagging the faces which are successfully detected.

Original languageEnglish
Title of host publication2nd International Conference on Computer, Communication, and Signal Processing
Subtitle of host publicationSpecial Focus on Technology and Innovation for Smart Environment, ICCCSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538611418
DOIs
Publication statusPublished - 30-08-2018
Event2nd International Conference on Computer, Communication, and Signal Processing, ICCCSP 2018 - Chennai, India
Duration: 22-02-201823-02-2018

Publication series

Name2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018

Conference

Conference2nd International Conference on Computer, Communication, and Signal Processing, ICCCSP 2018
CountryIndia
CityChennai
Period22-02-1823-02-18

Fingerprint

Face recognition
learning
marking
Neural networks
boom
Convolution
convolution integrals
histograms
platforms
Detectors
detectors
Deep learning

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Instrumentation

Cite this

Mehta, J., Ramnani, E., & Singh, S. (2018). Face Detection and Tagging Using Deep Learning. In 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018 [8452853] (2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCSP.2018.8452853
Mehta, Jinesh ; Ramnani, Eshaan ; Singh, Sanjay. / Face Detection and Tagging Using Deep Learning. 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018).
@inproceedings{85520276fa9445678a04f53d0be90cde,
title = "Face Detection and Tagging Using Deep Learning",
abstract = "With the social media boom in today's world, we see people constantly uploading photos of themselves along with their friends and family on various social media platforms such as Facebook, Instagram, Twitter, Google+, etc. What if they want to see all the photos in a categorized form such as photos with a particular person. In this paper, we extend the concept of Multiview Face Detection using Convolution Neural Networks (CNN) used by Farfade et al. by providing a tagging system for the detected faces. For the face detection, we use Deep Dense Face Detector, which uses a single model based on deep convolutional neural networks. All the detected faces are recognized using Local Binary Patterns Histograms (LBPH) method. Precision, recall, and F-measure are the parameters used to measure the performance of the algorithm. An accuracy of 85{\%} is achieved for tagging the faces which are successfully detected.",
author = "Jinesh Mehta and Eshaan Ramnani and Sanjay Singh",
year = "2018",
month = "8",
day = "30",
doi = "10.1109/ICCCSP.2018.8452853",
language = "English",
isbn = "9781538611418",
series = "2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2nd International Conference on Computer, Communication, and Signal Processing",
address = "United States",

}

Mehta, J, Ramnani, E & Singh, S 2018, Face Detection and Tagging Using Deep Learning. in 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018., 8452853, 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Computer, Communication, and Signal Processing, ICCCSP 2018, Chennai, India, 22-02-18. https://doi.org/10.1109/ICCCSP.2018.8452853

Face Detection and Tagging Using Deep Learning. / Mehta, Jinesh; Ramnani, Eshaan; Singh, Sanjay.

2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8452853 (2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Face Detection and Tagging Using Deep Learning

AU - Mehta, Jinesh

AU - Ramnani, Eshaan

AU - Singh, Sanjay

PY - 2018/8/30

Y1 - 2018/8/30

N2 - With the social media boom in today's world, we see people constantly uploading photos of themselves along with their friends and family on various social media platforms such as Facebook, Instagram, Twitter, Google+, etc. What if they want to see all the photos in a categorized form such as photos with a particular person. In this paper, we extend the concept of Multiview Face Detection using Convolution Neural Networks (CNN) used by Farfade et al. by providing a tagging system for the detected faces. For the face detection, we use Deep Dense Face Detector, which uses a single model based on deep convolutional neural networks. All the detected faces are recognized using Local Binary Patterns Histograms (LBPH) method. Precision, recall, and F-measure are the parameters used to measure the performance of the algorithm. An accuracy of 85% is achieved for tagging the faces which are successfully detected.

AB - With the social media boom in today's world, we see people constantly uploading photos of themselves along with their friends and family on various social media platforms such as Facebook, Instagram, Twitter, Google+, etc. What if they want to see all the photos in a categorized form such as photos with a particular person. In this paper, we extend the concept of Multiview Face Detection using Convolution Neural Networks (CNN) used by Farfade et al. by providing a tagging system for the detected faces. For the face detection, we use Deep Dense Face Detector, which uses a single model based on deep convolutional neural networks. All the detected faces are recognized using Local Binary Patterns Histograms (LBPH) method. Precision, recall, and F-measure are the parameters used to measure the performance of the algorithm. An accuracy of 85% is achieved for tagging the faces which are successfully detected.

UR - http://www.scopus.com/inward/record.url?scp=85054055329&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054055329&partnerID=8YFLogxK

U2 - 10.1109/ICCCSP.2018.8452853

DO - 10.1109/ICCCSP.2018.8452853

M3 - Conference contribution

SN - 9781538611418

T3 - 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018

BT - 2nd International Conference on Computer, Communication, and Signal Processing

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Mehta J, Ramnani E, Singh S. Face Detection and Tagging Using Deep Learning. In 2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8452853. (2nd International Conference on Computer, Communication, and Signal Processing: Special Focus on Technology and Innovation for Smart Environment, ICCCSP 2018). https://doi.org/10.1109/ICCCSP.2018.8452853