In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face images or new 3D face models can be registered automatically by computing dense one-to-one correspondence to an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces with an "unlikely" appearance. Starting from

. In this paper we propose a new approach for mapping and blending textures on 3D geometries. The system starts from a 3D mesh which represents a real object and improves this model with pictorial detail. Texture detail is acquired via a common photographic process directly from the real object. These images are then registered and stitched on the 3D mesh, by integrating them into a single standard texture map. An optimal correspondence between regions of the 3D mesh and sections of the acquired images is built. Then, a new approach is proposed to produce a smooth join between different images that map on adjacent sections of the surface, based on texture blending. For each mesh face which is on the adjacency border between different observed images, a corresponding triangular texture patch is resampled as a weighted blend of the corresponding adjacent images sections. The accuracy of the resampling and blending process is improved by computing an accurate piecewise local r...

A new system for the construction of highly realistic models of real free-form 3D objects is proposed, based on the integration of several techniques (automatic 3D scanning, inverse illumination, inverse texture-mapping and textured 3D graphics).Our system improves the quality of a 3D model (e.g. acquired with a range scanning device) by adding color detail and, if required, high frequency shape detail.Detail is obtained by processing a set of digital photographs of the object.This is carried out by performing several subtasks: to compute camera calibration and position, to remove illumination effects obtaining both illumination-invariant reflectance properties and a high resolution surface normal field, and finally to blend and stitch the acquired detail on the triangle mesh via standard texture mapping.In particular, the smooth join between different images that map on adjacent sections of the surface is obtained by applying an accurate piecewise local registration of the original images and by blending textures.For each mesh face which is on the adjacency border between different observed images, a corresponding triangular texture patch can also be resampled as a weighted blend of the corresponding adjacent image sections.Examples of the results obtained with sample works of art are presented and discussed.

The problem of building virtual models from sensor data increases in importance as powerful graphics rendering hardware becomes widespread. Model building stands at the interface between computer vision and computer graphics, and researchers from both areas have made contributions. We believe that only by a systematic review of the remaining open research question can further progress be made. This paper is an attempt at providing such a review. First, we describe the basic steps in the model building pipeline. Then we discuss the open problems that remain in each step. Finally, we describe some overall research themes that we believe should guide further work in this area.

y keyboard synthesizers. But the advent of sound sampling dramatically simplified the reproduction of high-fidelity natural sounds. Bill Buxton of the University of Toronto and Alias | Wavefront and other researchers recognized the analogy with computer graphics. The typical elements of computer graphics, including object shape and motion, surface texture, scene lighting, and camera position, can all be sampled from the physical world, resulting in higher-fidelity imagery and simplifying user involvement. With sampling technology, users can now either synthesize elements from scratch or sample the physical world. We take a slightly different perspective on synthesis and sampling, viewing all input devices as spatial samplers, at varying levels of abstraction, of the physical world. We examine sampling and synthesis issues relative to the abilities and compatibilities of spatial input devices used to accomplish a particular computer graphics task. How does spatial sampling support co