Masked correlation filters for partially occluded face recognition

Eric J. He; Joseph A. Fernandez; B. V. K. Vijaya Kumar; Mohamed I. Alkanhal

ICASSP 2016accepted0 citations

Masked correlation filters for partially occluded face recognition

Eric J. He, Joseph A. Fernandez, B. V. K. Vijaya Kumar, Mohamed I. Alkanhal

Abstract

Face recognition is widely used for a variety of applications, such as identifying people for security purposes, as well as photo album organization. A challenge is to perform accurate face recognition when there exist partial occlusions of the face such as scarves or sunglasses. Correlation Filters (CFs) are an occlusion-tolerant object recognition method, potentially suited to deal with partial occlusions. In this paper, we introduce a new class of correlation filters called Masked Correlation Filters (MCFs), that are designed specifically to handle partial occlusions in face images. The benefits of using MCFs are illustrated using well-known face image data sets.

BibTeX

@inproceedings{icassp2016_maskedcorrelatio,
  title = {Masked correlation filters for partially occluded face recognition},
  author = {Eric J. He and Joseph A. Fernandez and B. V. K. Vijaya Kumar and Mohamed I. Alkanhal},
  booktitle = {ICASSP 2016},
  year = {2016}
}