Kanonik korelasyon analizi ile robot resimden yüz tanima

Bekir Sȩn; Yakup Oz̈kazanç

doi:10.1109/SIU.2013.6531277

Kanonik korelasyon analizi ile robot resimden yüz tanima

Translated title of the contribution: Face-sketch recognition using canonical correlation analysis

Bekir Sȩn
, Yakup Oz̈kazanç

Division of Control and Command Systems

Akilli Sistemler Grubu

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

3 Citations (Scopus)

Abstract

Hand-drawn face sketches are frequently used in criminal investigations. In this paper, we present a novel framework for face recognition from sketches. Our framework based is on Principle Component Analysis (PCA) and Canonical Correlation Analysis (CCA). First, we apply PCA to a dataset for dimension reduction and then apply CCA for reaching maximum correlation within a dataset. This approach is tested on two different datasets including 311 photo-sketch pairs. The performance reached 99.36% recognition rate on these experiments.

Translated title of the contribution	Face-sketch recognition using canonical correlation analysis
Original language	Turkish
Title of host publication	2013 21st Signal Processing and Communications Applications Conference, SIU 2013
DOIs	https://doi.org/10.1109/SIU.2013.6531277
Publication status	Published - 2013
Event	2013 21st Signal Processing and Communications Applications Conference, SIU 2013 - Haspolat, Turkey Duration: 24 Apr 2013 → 26 Apr 2013

Publication series

Name	2013 21st Signal Processing and Communications Applications Conference, SIU 2013

Conference

Conference	2013 21st Signal Processing and Communications Applications Conference, SIU 2013
Country/Territory	Turkey
City	Haspolat
Period	24/04/13 → 26/04/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Access to Document

10.1109/SIU.2013.6531277

Cite this

@inproceedings{919c2d2de114414e9c5a6ee119fd9c2e,

title = "Kanonik korelasyon analizi ile robot resimden y{\"u}z tanima",

abstract = "Hand-drawn face sketches are frequently used in criminal investigations. In this paper, we present a novel framework for face recognition from sketches. Our framework based is on Principle Component Analysis (PCA) and Canonical Correlation Analysis (CCA). First, we apply PCA to a dataset for dimension reduction and then apply CCA for reaching maximum correlation within a dataset. This approach is tested on two different datasets including 311 photo-sketch pairs. The performance reached 99.36\% recognition rate on these experiments.",

author = "Bekir Sȩn and Yakup O{\"z}kazan{\c c}",

year = "2013",

doi = "10.1109/SIU.2013.6531277",

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

isbn = "9781467355629",

series = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",

booktitle = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",

note = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013 ; Conference date: 24-04-2013 Through 26-04-2013",

}

Sȩn, B & Oz̈kazanç, Y 2013, Kanonik korelasyon analizi ile robot resimden yüz tanima. in 2013 21st Signal Processing and Communications Applications Conference, SIU 2013., 6531277, 2013 21st Signal Processing and Communications Applications Conference, SIU 2013, 2013 21st Signal Processing and Communications Applications Conference, SIU 2013, Haspolat, Turkey, 24/04/13. https://doi.org/10.1109/SIU.2013.6531277

Kanonik korelasyon analizi ile robot resimden yüz tanima. / Sȩn, Bekir; Oz̈kazanç, Yakup.
2013 21st Signal Processing and Communications Applications Conference, SIU 2013. 2013. 6531277 (2013 21st Signal Processing and Communications Applications Conference, SIU 2013).

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

TY - GEN

T1 - Kanonik korelasyon analizi ile robot resimden yüz tanima

AU - Sȩn, Bekir

AU - Oz̈kazanç, Yakup

PY - 2013

Y1 - 2013

N2 - Hand-drawn face sketches are frequently used in criminal investigations. In this paper, we present a novel framework for face recognition from sketches. Our framework based is on Principle Component Analysis (PCA) and Canonical Correlation Analysis (CCA). First, we apply PCA to a dataset for dimension reduction and then apply CCA for reaching maximum correlation within a dataset. This approach is tested on two different datasets including 311 photo-sketch pairs. The performance reached 99.36% recognition rate on these experiments.

AB - Hand-drawn face sketches are frequently used in criminal investigations. In this paper, we present a novel framework for face recognition from sketches. Our framework based is on Principle Component Analysis (PCA) and Canonical Correlation Analysis (CCA). First, we apply PCA to a dataset for dimension reduction and then apply CCA for reaching maximum correlation within a dataset. This approach is tested on two different datasets including 311 photo-sketch pairs. The performance reached 99.36% recognition rate on these experiments.

UR - https://www.scopus.com/pages/publications/84880891769

U2 - 10.1109/SIU.2013.6531277

DO - 10.1109/SIU.2013.6531277

M3 - Konferans katkısı

AN - SCOPUS:84880891769

SN - 9781467355629

T3 - 2013 21st Signal Processing and Communications Applications Conference, SIU 2013

BT - 2013 21st Signal Processing and Communications Applications Conference, SIU 2013

T2 - 2013 21st Signal Processing and Communications Applications Conference, SIU 2013

Y2 - 24 April 2013 through 26 April 2013

ER -

Kanonik korelasyon analizi ile robot resimden yüz tanima

Abstract

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