Boosting 3D LBP-based face recognition by fusing shape and texture descriptors on the mesh

Claudio Tortorici, Naoufel Werghi, Stefano Berretti

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

11 Scopus citations

Abstract

In this paper, we present a novel approach for fusing shape and texture local binary patterns (LBP) for 3D face recognition. Using the framework proposed in [1], we compute LBP directly on the face mesh surface, then we construct a grid of the regions on the facial surface that can accommodate global and partial descriptions. Compared to its depth-image counterpart, our approach is distinguished by the following features: a) inherits the intrinsic advantages of mesh surface; b) does not require normalization; c) can accommodate partial matching. In addition, it allows early-level fusion of texture and shape modalities. Through experiments conducted on the BU-3DFE and Bosphorus databases, we assess different variants of our approach with regard to facial expressions and missing data.

Original languageBritish English
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherIEEE Computer Society
Pages2670-2674
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - 9 Dec 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 27 Sep 201530 Sep 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing, ICIP 2015
Country/TerritoryCanada
CityQuebec City
Period27/09/1530/09/15

Keywords

  • 3D face recognition
  • fusion
  • mesh-LBP

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