Kernel fusion of multiple histogram descriptors for robust face recognition

Chi-Ho Chan, Josef Kittler, Muhammad Tahir

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

11 Citations (Scopus)

Abstract

A multiple kernel fusion method combining two multiresolution histogram face descriptors is proposed to create a powerful representation method for face recognition. The multi resolution histogram descriptors are based on local binary patterns and local phase coding to achieve invariance to various types of image degradation. The multi-kernel fusion is based on the computationally efficient spectral regression KDA. The proposed face recognition method is evaluated on FRGC 2.0 database yielding very impressive results.
Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition
PublisherSpringer
Pages718-727
Volume6218
ISBN (Electronic)978-3-642-14980-1
ISBN (Print)978-3-642-14979-5
DOIs
Publication statusPublished - 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume6218

Keywords

  • Local binary pattern
  • local phase quantization
  • kernel
  • fusion
  • linear discriminant analysis

Fingerprint

Dive into the research topics of 'Kernel fusion of multiple histogram descriptors for robust face recognition'. Together they form a unique fingerprint.

Cite this