We present a 3D face animation method based on the morphable model. Given a facial image, the 3D face can be reconstructed automatically by the morphable model. So it is feasible to animate any face with the model. To construct the morphable model, a set of neutral 3D faces are acquired and aligned. A general parameterized animation model is constructed from expressive 3D faces and used to anim...

In this paper, we present a method to generate novel realistic 3D face model using a model trained from real 3D face data. 3D face samples are an important data platform for model training, algorithm design. Subject to the constraint of acquisition technology, sizes of current 3D face databases are relatively small and insufficient. The presented method is used to solve this problem. First real...

A fully automated 3D face reconstruction system for faces in 2D images is presented. It is implemented incorporating a method for facial feature detection into the initialization of the 3D face reconstruction process provided by Blanz et al.[2][3]. The initialization of that method takes alignments of previously selected facial feature points with their according vertices in the 3D face model. ...

Biometric measurements received an increasing interest for security applications in the last two decades. After the 911 terrorist attacks, face recognition has been an active research in this area. However, very few research group focus on face recognition from both 2D and 3D facial images. Almost all existing recognition systems rely on a single type of face information: 2D intensity (or color...

Many researches in face recognition have been dealing with the challenge of the great variability in head pose, lighting intensity and direction,facial expression, and aging. The main purpose of this overview is to describe the recent 3D face recognition algorithms. The last few years more and more 2D face recognition algorithms are improved and tested on less than perfect images. However, 3D m...

3D has become an important modality for face biometrics. The accuracy of a 3D face recognition system depends on a correct registration that aligns the facial surfaces and makes a comparison possible. The best results obtained so far use a one-to-all registration approach, which means each new facial surface is registered to all faces in the gallery, at a great computational cost. We explore th...

In this paper we present a method to derive 3D shape and surface texture of a human face from a single image. The method draws on a general flexible 3D face model which is “learned” from examples of individual 3D-face data (Cyberware-scans). In an analysis-by-synthesis loop, the flexible model is matched to the novel face image. From the coloured 3D model obtained by this procedure, we can gene...

The recognition performance of the conventional 3D face recognition algorithm using ICP (Iterative Closest Point) is degraded for the 3D face data with expression changes. Addressing this problem, we consider the use of the expression-invariant local regions of a face. We find the expression-invariant regions through the distance analysis between 3D face data with the neutral expression and smi...

In this paper, a precise and robust algorithm is presented to automatically model the 3D face with only single frontal face image. For shape and projection parameters estimation, an energy function is built to represent the difference between the approximate observed face 3D shape and estimated face 3D shape. To achieve more robust results, shape constraint is added to the energy function. For ...

Approaches for cross-pose face recognition can be categorized into 2D image based and 3D model based. However, only a small number of 3D model based approaches are reported although 3D information is considered crucial for cross-pose analysis. Extended from a latest face reconstruction method using a single 3D reference model, this study focuses on using the reconstructed 3D face for recognitio...