Matching caricatures to photographs

Bahri Abaci; Tayfun Akgul

doi:10.1007/s11760-015-0819-8

Matching caricatures to photographs

Bahri Abaci^*, Tayfun Akgul

^*Bu çalışma için yazışmadan sorumlu yazar

Elektronik ve Hab.Müh.Bölümü

Istanbul Technical University

Araştırma sonucu: Dergiye katkı › Makale › bilirkişi

19 Atıf (Scopus)

Özet

Facial caricatures are informative funny images that allow us to identify a subject even with a few lines and dots. Matching caricatures to photographs is a challenging cross-modal face matching problem. This paper addresses this problem by defining a set of qualitative face features both for caricatures and photographs where features are automatically extracted from photos and manually labeled in caricatures. Additionally we release a publicly available caricature-photograph database with 200 caricatures and corresponding photomates. In our experiments, we use genetic algorithms and logistic regression and achieve over (Formula presented.) recognition rate at 0.1 false accept rate.

Orijinal dil	İngilizce
Sayfa (başlangıç-bitiş)	295-303
Sayfa sayısı	9
Dergi	Signal, Image and Video Processing
Hacim	9
DOI'lar	https://doi.org/10.1007/s11760-015-0819-8
Yayın durumu	Yayınlandı - 1 Ara 2015

Bibliyografik not

Publisher Copyright:
© 2015, Springer-Verlag London.

Finansman

This work is supported by The Scientific and Technological Research Council of Turkey (TUBITAK), Project No: 112E142. The authors would like to thank Anil Jain, Brendon Klare, Serhat Bucak and Mehmet Kerem Turkcan for their interest, initial help and contribution.

Finansörler	Finansör numarası
TUBITAK	112E142
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Belgeye Erişim

10.1007/s11760-015-0819-8

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Matching caricatures to photographs",

abstract = "Facial caricatures are informative funny images that allow us to identify a subject even with a few lines and dots. Matching caricatures to photographs is a challenging cross-modal face matching problem. This paper addresses this problem by defining a set of qualitative face features both for caricatures and photographs where features are automatically extracted from photos and manually labeled in caricatures. Additionally we release a publicly available caricature-photograph database with 200 caricatures and corresponding photomates. In our experiments, we use genetic algorithms and logistic regression and achieve over (Formula presented.) recognition rate at 0.1 false accept rate.",

keywords = "Caricature recognition, Facial attributes, Genetic algorithms",

author = "Bahri Abaci and Tayfun Akgul",

note = "Publisher Copyright: {\textcopyright} 2015, Springer-Verlag London.",

year = "2015",

month = dec,

day = "1",

doi = "10.1007/s11760-015-0819-8",

language = "English",

volume = "9",

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AU - Abaci, Bahri

AU - Akgul, Tayfun

PY - 2015/12/1

Y1 - 2015/12/1

N2 - Facial caricatures are informative funny images that allow us to identify a subject even with a few lines and dots. Matching caricatures to photographs is a challenging cross-modal face matching problem. This paper addresses this problem by defining a set of qualitative face features both for caricatures and photographs where features are automatically extracted from photos and manually labeled in caricatures. Additionally we release a publicly available caricature-photograph database with 200 caricatures and corresponding photomates. In our experiments, we use genetic algorithms and logistic regression and achieve over (Formula presented.) recognition rate at 0.1 false accept rate.

AB - Facial caricatures are informative funny images that allow us to identify a subject even with a few lines and dots. Matching caricatures to photographs is a challenging cross-modal face matching problem. This paper addresses this problem by defining a set of qualitative face features both for caricatures and photographs where features are automatically extracted from photos and manually labeled in caricatures. Additionally we release a publicly available caricature-photograph database with 200 caricatures and corresponding photomates. In our experiments, we use genetic algorithms and logistic regression and achieve over (Formula presented.) recognition rate at 0.1 false accept rate.

KW - Caricature recognition

KW - Facial attributes

KW - Genetic algorithms

UR - http://www.scopus.com/inward/record.url?scp=84947487006&partnerID=8YFLogxK

U2 - 10.1007/s11760-015-0819-8

DO - 10.1007/s11760-015-0819-8

M3 - Article

AN - SCOPUS:84947487006

SN - 1863-1703

VL - 9

SP - 295

EP - 303

JO - Signal, Image and Video Processing

JF - Signal, Image and Video Processing

ER -

Matching caricatures to photographs

Özet

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap