Garuda: a deep learning based solution for capturing selfies safely

Jitender  Singh Virk; Abhinav Dhall

doi:10.1145/3308557.3308669

Garuda: a deep learning based solution for capturing selfies safely

Jitender Singh Virk, Abhinav Dhall

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

2 Citations (Scopus)

Abstract

Clicking selfies using mobile phones has become a trend in the past few years. It is documented that the thrill of clicking selfies at adventurous places has resulted in serious injuries and even death in some cases. To overcome this, we propose a system which can alert the user by detecting the level of danger in the background while capturing selfies. Our app is based on a deep Convolutional Neural Network (CNN). The prediction is performed as a 5 class classification problem with classes representing a different level of danger. Face detection and device orientation information are also used for robustness and lesser battery consumption.

Original language	English
Title of host publication	Proceedings of IUI 2019
Editors	Oliver Brdiczka, Gaëlle Calvary, Polo Chau
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	43-44
Number of pages	2
ISBN (Electronic)	9781450366731
DOIs	https://doi.org/10.1145/3308557.3308669 https://doi.org/10.1145/3308557.3308669
Publication status	Published - 16 Mar 2019
Externally published	Yes
Event	International Conference on Intelligent User Interfaces 2019 - Los Angeles, United States of America Duration: 16 Mar 2019 → 20 Mar 2019 Conference number: 24th http://iui.acm.org/2019/

Publication series

Name	International Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference	International Conference on Intelligent User Interfaces 2019
Abbreviated title	IUI 2019
Country/Territory	United States of America
City	Los Angeles
Period	16/03/19 → 20/03/19
Internet address	http://iui.acm.org/2019/

Keywords

Deep learning
Safe selfie
Scene analysis
Selfie

Access to Document

Cite this

Singh Virk, J., & Dhall, A. (2019). Garuda: a deep learning based solution for capturing selfies safely. In O. Brdiczka, G. Calvary, & P. Chau (Eds.), Proceedings of IUI 2019 (pp. 43-44). (International Conference on Intelligent User Interfaces, Proceedings IUI). Association for Computing Machinery (ACM). https://doi.org/10.1145/3308557.3308669, https://doi.org/10.1145/3308557.3308669

@inproceedings{2ea2dd4eed0548c4874e3d4e86cfdbc2,

title = "Garuda: a deep learning based solution for capturing selfies safely",

abstract = "Clicking selfies using mobile phones has become a trend in the past few years. It is documented that the thrill of clicking selfies at adventurous places has resulted in serious injuries and even death in some cases. To overcome this, we propose a system which can alert the user by detecting the level of danger in the background while capturing selfies. Our app is based on a deep Convolutional Neural Network (CNN). The prediction is performed as a 5 class classification problem with classes representing a different level of danger. Face detection and device orientation information are also used for robustness and lesser battery consumption.",

keywords = "Deep learning, Safe selfie, Scene analysis, Selfie",

author = "{Singh Virk}, Jitender and Abhinav Dhall",

year = "2019",

month = mar,

day = "16",

doi = "10.1145/3308557.3308669",

language = "English",

series = "International Conference on Intelligent User Interfaces, Proceedings IUI",

publisher = "Association for Computing Machinery (ACM)",

pages = "43--44",

editor = "Brdiczka, {Oliver } and Calvary, {Ga{\"e}lle } and Chau, {Polo }",

booktitle = "Proceedings of IUI 2019",

address = "United States of America",

note = "International Conference on Intelligent User Interfaces 2019, IUI 2019 ; Conference date: 16-03-2019 Through 20-03-2019",

url = "http://iui.acm.org/2019/",

}

Singh Virk, J & Dhall, A 2019, Garuda: a deep learning based solution for capturing selfies safely. in O Brdiczka, G Calvary & P Chau (eds), Proceedings of IUI 2019. International Conference on Intelligent User Interfaces, Proceedings IUI, Association for Computing Machinery (ACM), New York NY USA, pp. 43-44, International Conference on Intelligent User Interfaces 2019, Los Angeles, California, United States of America, 16/03/19. https://doi.org/10.1145/3308557.3308669, https://doi.org/10.1145/3308557.3308669

Garuda : a deep learning based solution for capturing selfies safely. / Singh Virk, Jitender ; Dhall, Abhinav.

Proceedings of IUI 2019. ed. / Oliver Brdiczka; Gaëlle Calvary; Polo Chau. New York NY USA : Association for Computing Machinery (ACM), 2019. p. 43-44 (International Conference on Intelligent User Interfaces, Proceedings IUI).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

TY - GEN

T1 - Garuda

T2 - International Conference on Intelligent User Interfaces 2019

AU - Singh Virk, Jitender

AU - Dhall, Abhinav

N1 - Conference code: 24th

PY - 2019/3/16

Y1 - 2019/3/16

N2 - Clicking selfies using mobile phones has become a trend in the past few years. It is documented that the thrill of clicking selfies at adventurous places has resulted in serious injuries and even death in some cases. To overcome this, we propose a system which can alert the user by detecting the level of danger in the background while capturing selfies. Our app is based on a deep Convolutional Neural Network (CNN). The prediction is performed as a 5 class classification problem with classes representing a different level of danger. Face detection and device orientation information are also used for robustness and lesser battery consumption.

AB - Clicking selfies using mobile phones has become a trend in the past few years. It is documented that the thrill of clicking selfies at adventurous places has resulted in serious injuries and even death in some cases. To overcome this, we propose a system which can alert the user by detecting the level of danger in the background while capturing selfies. Our app is based on a deep Convolutional Neural Network (CNN). The prediction is performed as a 5 class classification problem with classes representing a different level of danger. Face detection and device orientation information are also used for robustness and lesser battery consumption.

KW - Deep learning

KW - Safe selfie

KW - Scene analysis

KW - Selfie

UR - http://www.scopus.com/inward/record.url?scp=85074449106&partnerID=8YFLogxK

U2 - 10.1145/3308557.3308669

DO - 10.1145/3308557.3308669

M3 - Conference Paper

AN - SCOPUS:85074449106

T3 - International Conference on Intelligent User Interfaces, Proceedings IUI

SP - 43

EP - 44

BT - Proceedings of IUI 2019

A2 - Brdiczka, Oliver

A2 - Calvary, Gaëlle

A2 - Chau, Polo

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

Y2 - 16 March 2019 through 20 March 2019

ER -

Singh Virk J, Dhall A. Garuda: a deep learning based solution for capturing selfies safely. In Brdiczka O, Calvary G, Chau P, editors, Proceedings of IUI 2019. New York NY USA: Association for Computing Machinery (ACM). 2019. p. 43-44. (International Conference on Intelligent User Interfaces, Proceedings IUI). https://doi.org/10.1145/3308557.3308669, https://doi.org/10.1145/3308557.3308669

Garuda: a deep learning based solution for capturing selfies safely

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Cite this