3D face verification across pose based on euler rotation and tensors
|Author:||Chouchane, Ammar1; Ouamane, Abdelmalik1; Boutellaa, Elhocine2;|
1Université de Biskra, Biskra, Algeria
2Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
3Institut Fresnel, Université de Marseille, Marseille, France
|Online Access:||PDF Full Text (PDF, 0.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019091328157
|Publish Date:|| 2019-09-13
In this paper, we propose a new approach for 3D face verification based on tensor representation. Face challenges, such as illumination, expression and pose, are modeled as a multilinear algebra problem where facial images are represented as high order tensors. Particularly, to account for head pose variations, several pose scans are generated from a single depth image using Euler transformation. Multi-bloc local phase quantization (MB-LPQ) histogram features are extracted from depth face images and arranged as a third order tensor. The dimensionality of the tensor is reduced based on the higher-order singular value decomposition (HOSVD). HOSVD projects the input tensor in a new subspace in which the dimension of each tensor mode is reduced. To discriminate faces of different persons, we utilize the Enhanced Fisher Model (EFM). Experimental evaluations on CASIA-3D database, which contains large head pose variations, demonstrate the effectiveness of the proposed approach. A verification rate of 98.60% is obtained.
Multimedia tools and applications
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
© Springer Science+Business Media, LLC, part of Springer Nature 2017. This is a post-peer-review, pre-copyedit version of an article published in Multimed Tools Appl. The final authenticated version is available online at: https://doi.org/10.1007/s11042-017-5478-z.