2861998
Reanimating the dead: reconstruction of expressive faces from skull data
Facial reconstruction for postmortem identification of humans from their skeletal remains is a challenging and fascinating part of forensic art. The former look of a face can be approximated by predicting and modeling the layers of tissue on the skull. This work is as of today carried out solely by physical sculpting with clay, where experienced artists invest up to hundreds of hours to craft a reconstructed face model. Remarkably, one of the most popular tissue reconstruction methods bears many resemblances with surface fitting techniques used in computer graphics, thus suggesting the possibility of a transfer of the manual approach to the computer. In this paper, we present a facial reconstruction approach that fits an anatomy-based virtual head model, incorporating skin and muscles, to a scanned skull using statistical data on skull / tissue relationships. The approach has many advantages over the traditional process: a reconstruction can be completed in about an hour from acquired skull data; also, variations such as a slender or a more obese build of the modeled individual are easily created. Last not least, by matching not only skin geometry but also virtual muscle layers, an animatable head model is generated that can be used to form facial expressions beyond the neutral face typically used in physical reconstructions.
12345789
Vector field based shape deformations
We present an approach to define shape deformations by constructing and interactively modifying C1 continuous time-dependent divergence-free vector fields. The deformation is obtained by a path line integration of the mesh vertices. This way, the deformation is volume-preserving, free of (local and global) self-intersections, feature preserving, smoothness preserving, and local. Different modeling metaphors support the approach which is able to modify the vector field on-the-fly according to the user input. The approach works at interactive frame rates for moderate mesh sizes, and the numerical integration preserves the volume with a high accuracy.
207161594
Perception-motivated high dynamic range video encoding
Due to rapid technological progress in high dynamic range (HDR) video capture and display, the efficient storage and transmission of such data is crucial for the completeness of any HDR imaging pipeline. We propose a new approach for inter-frame encoding of HDR video, which is embedded in the well-established MPEG-4 video compression standard. The key component of our technique is luminance quantization that is optimized for the contrast threshold perception in the human visual system. The quantization scheme requires only 10--11 bits to encode 12 orders of magnitude of visible luminance range and does not lead to perceivable contouring artifacts. Besides video encoding, the proposed quantization provides perceptually-optimized luminance sampling for fast implementation of any global tone mapping operator using a lookup table. To improve the quality of synthetic video sequences, we introduce a coding scheme for discrete cosine transform (DCT) blocks with high contrast. We demonstrate the capabilities of HDR video in a player, which enables decoding, tone mapping, and applying post-processing effects in real-time. The tone mapping algorithm as well as its parameters can be changed interactively while the video is playing. We can simulate post-processing effects such as glare, night vision, and motion blur, which appear very realistic due to the usage of HDR data.
2803614
Exchanging Faces in Images
Pasting somebody’s face into an existing image with traditional photo retouching and digital image processing tools has only been possible if both images show the face from the same viewpoint and with the same illumination. However, this is rarely the case for given pairs of images. We present a system that exchanges faces across large differences in viewpoint and illumination. It is based on an algorithm that estimates 3D shape and texture along with all relevant scene parameters, such as pose and lighting, from single images. Manual interaction is reduced to clicking on a set of about 7 feature points, and marking the hairline in the target image. The system can be used for image processing, virtual try-on of hairstyles, and face recognition. By separating face identity from imaging conditions, our approach provides an abstract representation of images and a novel, high-level tool for image manipulation.
6976029
Extracting higher order critical points and topological simplification of 3D vector fields
This paper presents an approach to extracting and classifying higher order critical points of 3D vector fields. To do so, we place a closed convex surface s around the area of interest. Then we show that the complete 3D classification of a critical point into areas of different flow behavior is equivalent to extracting the topological skeleton of an appropriate 2D vector field on s, if each critical point is equipped with an additional bit of information. Out of this skeleton, we create an icon which replaces the complete topological structure inside s for the visualization. We apply our method to find a simplified visual representation of clusters of critical points, leading to expressive visualizations of topologically complex 3D vector fields.
2168693
Thrifty Final Gather for Radiosity
Finite Element methods are well suited to the computation of the light distribution in mostly diffuse scenes, but the resulting mesh is often far from optimal to accurately represent illumination. Shadow boundaries are hard to capture in the mesh, and the illumination may contain artifacts due to light transports at different mesh hierarchy levels. To render a high quality image a costly final gather reconstruction step is usually done, which re-evaluates the illumination integral for each pixel. In this paper an algorithm is presented which significantly speeds up the final gather by exploiting spatial and directional coherence information taken from the radiosity solution. Senders are classified, so that their contribution to a pixel is either interpolated from the radiosity solution or recomputed with an appropriate number of new samples. By interpolating this sampling pattern over the radiosity mesh, continuous solutions are obtained.