LFHOG: A discriminative descriptor for live face detection from light field image

Zhe Ji, Hao Zhu, Qing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

30 Scopus citations

Abstract

How to avoid the invading of the attack in the biometric system, such as 2D printed photos, gradually becomes an important research hotspot. In this paper, we present a novel descriptor in light field to tackle the issue. Based on the angular and spatial information in light field, the proposed light field histogram of gradient (LFHoG) descriptor is derived from three directions, including vertical, horizontal and depth. Different with traditional HoG in 2D image, the gradient in depth direction is distinctive in light field. To validate the effectiveness of the proposed LFHoG descriptor, experiments have been carried out on light field datasets taken by a Lytro camera. The descriptor can achieve 99.75% accuracy on the user collected dataset, which proves the correctness and effectiveness of the LFHoG descriptor.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages1474-1478
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - 3 Aug 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
Country/TerritoryUnited States
CityPhoenix
Period25/09/1628/09/16

Keywords

  • Face detection
  • Light field
  • Light field histogram of gradient (LFHoG)
  • Live face

Fingerprint

Dive into the research topics of 'LFHOG: A discriminative descriptor for live face detection from light field image'. Together they form a unique fingerprint.

Cite this