Computer Vision And Pattern Analysis Laboratory Home Page  Home
People  People
Publications  Publications
Publications  Databases
Contact Information  Contact
Supported Research Projects  Supported Research Projects
Research Activites  Research Activites
Research Groups
SPIS - Signal Processing and Information Systems Lab.SPIS - Signal Processing and Information Systems Lab.
Medical Vision and Analysis Group  Medical Research Activities
Biometrics Research Group  Biometrics Research Group
SPIS - Signal Processing and Information Systems Lab.MISAM - Machine Intelligence for Speech Audio and Multimedia.
Knowledge Base
  Paper Library
Local Binary Pattern Domain Local Appearance Face Recognition (in Turkish)
Authors: H.K. Ekenel, M. Fischer, E. Tekeli, R. Stiefelhagen, A. Ercil
Published in: SIU 2008
Publication year: 2008
Abstract: This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images. The underlying idea is to benefit from both the robust image representation capability of local binary patterns, and the compact representation capability of local appearance-based face recognition. In the proposed method, prior to local appearance modeling, the input face image is transformed into the local binary pattern domain. The obtained LBP- representation is then decomposed into non-overlapping blocks and on each local block the discrete cosine transform is applied to extract the local features. The extracted local features are then concatenated to construct the overall feature vector. The proposed algorithm is tested extensively on the face images from the CMU PIE and the FRGC version 2 face databases. The experimental results show that the combined approach improves the performance significantly.
  download full paper

Home Back