3D face texture modeling from uncalibrated frontal and profile images

Abstract

Abstract3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many applications, for example, law enforcement, multi-view face images are usually captured for a subject during enrollment, which makes it desirable to build a 3D face texture model, given a pair of frontal and profile face images. We first determine the correspondence between uncalibrated frontal and profile face images through facial landmark alignment. An initial 3D face shape is then reconstructed from the frontal face image, followed by shape refinement utilizing the depth information provided by the profile image. Finally, face texture is extracted by mapping the frontal face image on the recovered 3D face shape. The proposed method is utilized for 2D face recognition in two scenarios: (i) normalization of probe image, and (ii) enhancing the representation capability of gallery set. Experimental results comparing the proposed method with a state-of-the-art commercial face matcher and densely sampled LBP on a subset of the FERET database show the effectiveness of the proposed 3D face texture model.

A Comprehensive Survey on Pose-Invariant Face Recognition

“…Similarly, Han and Jain (2012) extended the GEM approach to utilize the complementary information incorporated in the frontal and profile image pair. Their approach is based on Eq.…”

“…22 can also be relieved with various multi-stage strategies. For example, (Kang et al 2008;Hu et al 2012) proposed the multi-resolution fitting methods that fit the 3DMM model to the down-sampled low-resolution images and the original high-resolution image, successively. Aldrian and Smith (2013) proposed the sequential estimation of shape and texture parameters.…”

Evaluation of Face Recognition Methods in Unconstrained Environments

“…Carlos et al 37 , proposed a method for making the process of gallery maintenance making more efficient, which is based on one-against-some classification rule. Han et al 38 , proposed a 3D face texture modeling method using frontal and profile face images. The 2D face recognition has been also utilized in different scenarios.…”

Automatic multi-view face recognition via 3D model based pose regularization

“…Under these circumstances, 3D face models reconstructed from frontal face images can be the substitutions for real 3D faces. 3D Morphable Model and 3D generic elastic model (3D GEM), are typical approaches [12,28] used for generating non-frontal images from frontal views.…”