DCT Based Facial Feature Extraction

Author

Akakin, Hatice Cinar ; Sankur, Bülent

Author_Institution

Elektrik ve Elektron. Muhendisligi Bolumu, Bogazici Univ., Istanbul

fYear

2006

fDate

17-19 April 2006

Firstpage

1

Lastpage

4

Abstract

In this paper we introduced an automatic landmarking method for near-frontal face images based on DCT coefficients. The face information is provided as 480times640 gray-level images with 3D scene depth data. Range data is used to eliminate the background data from the face. The proposed facial landmarking algorithm uses a coarse-to-fine searching algorithm. In coarse level the images are downsampled to 80times60 pixels resolution. Both in coarse and fine levels SVM classifiers are trained using the DCT coefficients extracted from the manually landmarked training data. Coarse level candidate facial points are searched within the whole face image. Once the candidate locations are established, we revert back to the higher resolution image and refine the accuracy by using search windows around the coarse landmark locations

Keywords

discrete cosine transforms; face recognition; feature extraction; image resolution; image sampling; support vector machines; DCT coefficient; SVM classifier; coarse-fine searching algorithm; discrete cosine transform; facial feature extraction; facial landmarking algorithm; image resolution; image sampling; support vector machine; Data mining; Discrete cosine transforms; Facial features; Image resolution; Independent component analysis; Layout; Principal component analysis; Support vector machine classification; Support vector machines; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications, 2006 IEEE 14th

Conference_Location

Antalya

Print_ISBN

1-4244-0238-7

Type

conf

DOI

10.1109/SIU.2006.1659699

Filename

1659699