This paper presents a novel approach to aid face recognition: Using multiple views of a face, we construct a 3D model instead of directly using the 2D images for recognition. Our framework is designed for videos, which contain many instances of a target face from a sequence of slightly differing views, as opposed to a single static picture of the face. Specifically, we reconstruct the 3D face s...

We present a novel approach to pose and illumination invariant face recognition that combines two recent advances in the computer vision field: component-based recognition and 3D morphable models. In a first step a 3D morphable model is used to generate 3D face models from only two input images from each person in the training database. By rendering the 3D models under varying pose and illumina...

The creation of realistic 3D face models is still a fundamental problem in computer graphics. In this paper we present a novel method to obtain the 3D shape of an arbitrary human face using a sequence of silhouette images as input. Our face model is a linear combination of eigenheads, which are obtained by a Principal Component Analysis (PCA) of laser-scanned 3D human faces. The coefficients of...

3D face reconstruction from a single image is challenging problem, especially under partial occlusions and extreme poses. This because the uncertainty of estimated 2D landmarks will affect quality reconstruction. In this paper, we propose novel joint optimization method to adaptively reconstruct shapes image, which combines depths solve uncertain detections invisible landmarks. The strategy our...

Face recognition has been an interesting issue in pattern recognition over the past few decades. In this paper, we propose a new method for face recognition using 3D information. During preprocessing, the scanned 3D point clouds are first registered together, and at the same time, the regular meshes are generated. Then the novel shape variation representation based on GaussianHermite moments (G...

The Representational Power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. In this contribution, a novel approach is proposed to increase the RP of the 3D reconstruction PCA-based model by deforming a set of examples in the training dataset. By adding these deformed samples together with the original training samples we gain more RP. A 3D PCA-...

We present data collection and recognition experiment focused on multi-view face recognition/descriptor. Many face databases and face recognition systems have been constructed and experimented in terms of various illumination, time, poses, or expressions. However none of databases yet satisfies a large variation of poses to study systematic 3D human face information, which results unsatisfactor...

Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face rec...

Introduction: Automatic 3D face synthesis plays a crucial role in many applications. One example is real-time 3D model-based video coding. Here, a generic 3D face model should ideally be adapted automatically to a human face in the first video frame. Additionally, facial texture should be acquired without supervision. However, the time-consuming 3D scanner [1] is not accepted for such an automa...

As a classic statistical model of 3D facial shape and texture, 3D Morphable Model (3DMM) is widely used in facial analysis, e.g., model fitting, image synthesis. Conventional 3DMM is learned from a set of well-controlled 2D face images with associated 3D face scans, and represented by two sets of PCA basis functions. Due to the type and amount of training data, as well as the linear bases, the ...