5,041 research outputs found
A New 3D Tool for Planning Plastic Surgery
Face plastic surgery (PS) plays a major role in today medicine. Both for reconstructive and cosmetic surgery, achieving harmony of facial features is an important, if not the major goal. Several systems have been proposed for presenting to patient and surgeon possible outcomes of the surgical procedure. In this paper, we present a new 3D system able to automatically suggest, for selected facial features as nose, chin, etc, shapes that aesthetically match the patient's face. The basic idea is suggesting shape changes aimed to approach similar but more harmonious faces. To this goal, our system compares the 3D scan of the patient with a database of scans of harmonious faces, excluding the feature to be corrected. Then, the corresponding features of the k most similar harmonious faces, as well as their average, are suitably pasted onto the patient's face, producing k+1 aesthetically effective surgery simulations. The system has been fully implemented and tested. To demonstrate the system, a 3D database of harmonious faces has been collected and a number of PS treatments have been simulated. The ratings of the outcomes of the simulations, provided by panels of human judges, show that the system and the underlying idea are effectiv
Morphing of Geometric Composites via Residual Swelling
Understanding and controlling the shape of thin, soft objects has been the
focus of significant research efforts among physicists, biologists, and
engineers in the last decade. These studies aim to utilize advanced materials
in novel, adaptive ways such as fabricating smart actuators or mimicking living
tissues. Here, we present the controlled growth--like morphing of 2D sheets
into 3D shapes by preparing geometric composite structures that deform by
residual swelling. The morphing of these geometric composites is dictated by
both swelling and geometry, with diffusion controlling the swelling-induced
actuation, and geometric confinement dictating the structure's deformed shape.
Building on a simple mechanical analog, we present an analytical model that
quantitatively describes how the Gaussian and mean curvatures of a thin disk
are affected by the interplay among geometry, mechanics, and swelling. This
model is in excellent agreement with our experiments and numerics. We show that
the dynamics of residual swelling is dictated by a competition between two
characteristic diffusive length scales governed by geometry. Our results
provide the first 2D analog of Timoshenko's classical formula for the thermal
bending of bimetallic beams - our generalization explains how the Gaussian
curvature of a 2D geometric composite is affected by geometry and elasticity.
The understanding conferred by these results suggests that the controlled
shaping of geometric composites may provide a simple complement to traditional
manufacturing techniques
Techniques for augmenting the visualisation of dynamic raster surfaces
Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series
Transport-Based Neural Style Transfer for Smoke Simulations
Artistically controlling fluids has always been a challenging task.
Optimization techniques rely on approximating simulation states towards target
velocity or density field configurations, which are often handcrafted by
artists to indirectly control smoke dynamics. Patch synthesis techniques
transfer image textures or simulation features to a target flow field. However,
these are either limited to adding structural patterns or augmenting coarse
flows with turbulent structures, and hence cannot capture the full spectrum of
different styles and semantically complex structures. In this paper, we propose
the first Transport-based Neural Style Transfer (TNST) algorithm for volumetric
smoke data. Our method is able to transfer features from natural images to
smoke simulations, enabling general content-aware manipulations ranging from
simple patterns to intricate motifs. The proposed algorithm is physically
inspired, since it computes the density transport from a source input smoke to
a desired target configuration. Our transport-based approach allows direct
control over the divergence of the stylization velocity field by optimizing
incompressible and irrotational potentials that transport smoke towards
stylization. Temporal consistency is ensured by transporting and aligning
subsequent stylized velocities, and 3D reconstructions are computed by
seamlessly merging stylizations from different camera viewpoints.Comment: ACM Transaction on Graphics (SIGGRAPH ASIA 2019), additional
materials: http://www.byungsoo.me/project/neural-flow-styl
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