Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi

Emre Sercan Aslan; Baris Bayram; Gokhan Ince

doi:10.1109/SIU.2017.7960393

Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi

Translated title of the contribution: Distributed face recognition system for indoor environments

Emre Sercan Aslan^*, Baris Bayram, Gokhan Ince

^*Corresponding author for this work

Department of Computer Engineering

Istanbul Technical University

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

1 Citation (Scopus)

Abstract

Performance of a face recognition process changes depending on the distance between the camera and the person, light in the environment, pose, quality of image and the algorithm that is used for face recognition. An image collection system with a distributed architecture incorporating an embedded computer with a camera and a mobile robot equipped with a camera, a depth sensor and a microphone is developed. Face recognition using deep learning and artificial neural networks is applied on the gathered images. The performance of face recognition is investigated in terms of distance, size of the image set, activation mode, behaviour of the mobile robot and combination of the all components. The effectiveness of the system is verified using real world experiments.

Translated title of the contribution	Distributed face recognition system for indoor environments
Original language	Turkish
Title of host publication	2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509064946
DOIs	https://doi.org/10.1109/SIU.2017.7960393
Publication status	Published - 27 Jun 2017
Event	25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017

Publication series

Name	2017 25th Signal Processing and Communications Applications Conference, SIU 2017

Conference

Conference	25th Signal Processing and Communications Applications Conference, SIU 2017
Country/Territory	Turkey
City	Antalya
Period	15/05/17 → 18/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Access to Document

10.1109/SIU.2017.7960393

Cite this

Aslan, E. S., Bayram, B., & Ince, G. (2017). Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 Article 7960393 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2017.7960393

@inproceedings{03c2230fe0eb4c40956bd19d9139671d,

title = "Kapali Ortamlar İ{\c c}in Daǧitik Mimarili Y{\"u}z Tanima Sistemi",

abstract = "Performance of a face recognition process changes depending on the distance between the camera and the person, light in the environment, pose, quality of image and the algorithm that is used for face recognition. An image collection system with a distributed architecture incorporating an embedded computer with a camera and a mobile robot equipped with a camera, a depth sensor and a microphone is developed. Face recognition using deep learning and artificial neural networks is applied on the gathered images. The performance of face recognition is investigated in terms of distance, size of the image set, activation mode, behaviour of the mobile robot and combination of the all components. The effectiveness of the system is verified using real world experiments.",

keywords = "deep learning, distributed systems, face recognition, human-robot interaction, neural networks",

author = "Aslan, {Emre Sercan} and Baris Bayram and Gokhan Ince",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 25th Signal Processing and Communications Applications Conference, SIU 2017 ; Conference date: 15-05-2017 Through 18-05-2017",

year = "2017",

month = jun,

day = "27",

doi = "10.1109/SIU.2017.7960393",

language = "T{\"u}rk{\c c}e",

series = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

address = "United States",

}

Aslan, ES, Bayram, B & Ince, G 2017, Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi. in 2017 25th Signal Processing and Communications Applications Conference, SIU 2017., 7960393, 2017 25th Signal Processing and Communications Applications Conference, SIU 2017, Institute of Electrical and Electronics Engineers Inc., 25th Signal Processing and Communications Applications Conference, SIU 2017, Antalya, Turkey, 15/05/17. https://doi.org/10.1109/SIU.2017.7960393

Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi. / Aslan, Emre Sercan; Bayram, Baris; Ince, Gokhan.
2017 25th Signal Processing and Communications Applications Conference, SIU 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7960393 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017).

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

TY - GEN

T1 - Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi

AU - Aslan, Emre Sercan

AU - Bayram, Baris

AU - Ince, Gokhan

PY - 2017/6/27

Y1 - 2017/6/27

N2 - Performance of a face recognition process changes depending on the distance between the camera and the person, light in the environment, pose, quality of image and the algorithm that is used for face recognition. An image collection system with a distributed architecture incorporating an embedded computer with a camera and a mobile robot equipped with a camera, a depth sensor and a microphone is developed. Face recognition using deep learning and artificial neural networks is applied on the gathered images. The performance of face recognition is investigated in terms of distance, size of the image set, activation mode, behaviour of the mobile robot and combination of the all components. The effectiveness of the system is verified using real world experiments.

AB - Performance of a face recognition process changes depending on the distance between the camera and the person, light in the environment, pose, quality of image and the algorithm that is used for face recognition. An image collection system with a distributed architecture incorporating an embedded computer with a camera and a mobile robot equipped with a camera, a depth sensor and a microphone is developed. Face recognition using deep learning and artificial neural networks is applied on the gathered images. The performance of face recognition is investigated in terms of distance, size of the image set, activation mode, behaviour of the mobile robot and combination of the all components. The effectiveness of the system is verified using real world experiments.

KW - deep learning

KW - distributed systems

KW - face recognition

KW - human-robot interaction

KW - neural networks

UR - http://www.scopus.com/inward/record.url?scp=85026309551&partnerID=8YFLogxK

U2 - 10.1109/SIU.2017.7960393

DO - 10.1109/SIU.2017.7960393

M3 - Konferans katkısı

AN - SCOPUS:85026309551

T3 - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th Signal Processing and Communications Applications Conference, SIU 2017

Y2 - 15 May 2017 through 18 May 2017

ER -

Kapali Ortamlar İçin Daǧitik Mimarili Yüz Tanima Sistemi

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this