Boosting 3D LBP-Based Face Recognition by Fusing Shape and Texture Descriptors on the Mesh

Naoufel Werghi, Claudio Tortorici, Stefano Berretti, Alberto Del Bimbo

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

In this paper, we present a novel approach for fusing shape and texture local binary patterns (LBPs) on a mesh for 3D face recognition. Using a recently proposed framework, 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 with its depth-image counterpart, our approach is distinguished by the following features: 1) inherits the intrinsic advantages of mesh surface (e.g., preservation of the full geometry); 2) does not require normalization; and 3) 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, also in comparison to the state-of-the-art solutions.

Original languageBritish English
Article number7373633
Pages (from-to)964-979
Number of pages16
JournalIEEE Transactions on Information Forensics and Security
Volume11
Issue number5
DOIs
StatePublished - May 2016

Keywords

  • 3D face recognition
  • feature and score fusion
  • mesh-LBP

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