DocumentCode
607649
Title
Face-sketch recognition using canonical correlation analysis
Author
Sen, Baha ; Ozkazanc, Y.
Author_Institution
Akilli Sistemler Grubu, Karel Elektron., Ankara, Turkey
fYear
2013
fDate
24-26 April 2013
Firstpage
1
Lastpage
4
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.
Keywords
face recognition; principal component analysis; CCA; PCA; canonical correlation analysis; criminal investigations; dimension reduction; face-sketch recognition; hand-drawn face sketches; photo-sketch pairs; principle component analysis; Correlation; Face; Face recognition; Forensics; Principal component analysis; Robots; TV;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location
Haspolat
Print_ISBN
978-1-4673-5562-9
Electronic_ISBN
978-1-4673-5561-2
Type
conf
DOI
10.1109/SIU.2013.6531277
Filename
6531277
Link To Document