In this paper, a new approach to modelling 3D faces based on 2D images is introduced. Here 3D faces are created using two photographs from which we extract facial features based on image manipulation techniques. Through the image manipulation techniques we extract the crucial feature lines of the face in two views. These are then used in modifying a template base mesh which is created in 3D. This base mesh, which has been designed by keeping facial animation in mind, is then subdivided to provide the level of detail required. The methodology, as it stands, is semi-automatic whereby our goal is to automate this process in order to provide an inexpensive and expedient way of producing realistic face models intended for animation purposes. Thus, we show how image manipulation techniques can be used to create binary images which can in turn be used in manipulating a base mesh that can be adapted to a given facial geometry. In order to explain our approach more clearly we discuss a series of examples where we create 3D facial geometry of individuals given the corresponding image data.

This paper discusses how a boundary-based surface fitting approach can be utilised to smoothly reconstruct a given human face where the scan data corresponding to the face is provided. In particular, the paper discusses how a solution to the Biharmonic equation can be used to set up the corresponding boundary value problem. We show how a compact explicit solution method can be utilised for efficiently solving the chosen Biharmonic equation. Thus, given the raw scan data of a 3D face, we extract a series of profile curves from the data which can then be utilised as boundary conditions to solve the Biharmonic equation. The resulting solution provides us a continuous single surface patch describing the original face.

Yes / An important issue in many of today's biometric applications is the development of efficient and accurate techniques for representing related 3D data. Such data is often available through the process of digitization of complex geometric objects which are of importance to biometric applications. For example, in the area of 3D face recognition a digital point cloud of data corresponding to a given face is usually provided by a 3D digital scanner. For efficient data storage and for identification/authentication in a timely fashion such data requires to be represented using a few parameters or variables which are meaningful. Here we show how mathematical techniques based on Partial Differential Equations (PDEs) can be utilized to represent complex 3D data where the data can be parameterized in an efficient way. For example, in the case of a 3D face we show how it can be represented using PDEs whereby a handful of key facial parameters can be identified for efficient storage and verification.