1,721,131 research outputs found
RELIGHT: A compact and accurate RTI representation for the web
No full textRelightable images have been widely used as a valuable tool in Cultural Heritage (CH) artifacts, including coins, bas-reliefs, paintings, and epigraphs. Reflection Transformation Imaging (RTI), a commonly used type of relightable images, consists of a per-pixel function which encodes the reflection behavior, estimated from a set of digital photographs acquired from a fixed view. Web visualisation tools for RTI images currently require to transmit substantial quantities of data in order to achieve high fidelity renderings. We propose a web-friendly compact representation for RTI images based on a joint interpolation-compression scheme that combines a PCA-based data reduction with a Gaussian Radial Basis Function (RBF) interpolation exhibiting superior performance in terms of quality/size ratio. This approach can be adapted also to other data interpolation schemes, and it is not limited to Gaussian RBF. The rendering part is simple to implement and computationally efficient allowing real-time rendering on low-end devices
Two examples of GPGPU acceleration of memory-intensive algorithm
No full textThe advent of GPGPU technologies has allowed for sensible speed-ups in many high-dimension, memory-intensive computational problems. In this paper we demonstrate the effectiveness of such techniques by describing two applications of GPGPU computing to two different subfields of computer graphics, namely computer vision and mesh processing. In the first case, CUDA technology is employed to accelerate the computation of approximation of motion between two images, known also as optical flow. As for mesh processing, we exploit the massively parallel architecture of CUDA devices to accelerate the face clustering procedure that is employed in many recent mesh segmentation algorithms. In both cases, the results obtained so far are presented and thoroughly discussed, along with the expected future development of the work
An Interactive Local Flattening Operator to Support Digital Investigations on Artwork Surfaces
No full textAnalyzing either high-frequency shape detail or any other 2D fields (scalar or vector) embedded over a 3D geometry is a complex task, since detaching the detail from the overall shape can be tricky. An alternative approach is to move to the 2D space, resolving shape reasoning to easier image processing techniques. In this paper we propose a novel framework for the analysis of 2D information distributed over 3D geometry, based on a locally smooth parametrization technique that allows us to treat local 3D data in terms of image content. The proposed approach has been implemented as a sketch-based system that allows to design with a few gestures a set of (possibly overlapping) parameterizations of rectangular portions of the surface. We demonstrate that, due to the locality of the parametrization, the distortion is under an acceptable threshold, while discontinuities can be avoided since the parametrized geometry is always homeomorphic to a disk. We show the effectiveness of the proposed technique to solve specific Cultural Heritage (CH) tasks: the analysis of chisel marks over the surface of a unfinished sculpture and the local comparison of multiple photographs mapped over the surface of an artwork. For this very difficult task, we believe that our framework and the corresponding tool are the first steps toward a computer-based shape reasoning system, able to support CH scholars with a medium they are more used to
Presentation of 3D Scenes Through Video Example
No full textUsing synthetic videos to present a 3D scene is a common requirement for architects, designers, engineers or Cultural Heritage professionals however it is usually time consuming and, in order to obtain high quality results, the support of a film maker/computer animation expert is necessary. We introduce an alternative approach that takes the 3D scene of interest and an example video as input, and automatically produces a video of the input scene that resembles the given video example. In other words, our algorithm allows the user to "replicate" an existing video, on a different 3D scene. We build on the intuition that a video sequence of a static environment is strongly characterized by its optical flow, or, in other words, that two videos are similar if their optical flows are similar. We therefore recast the problem as producing a video of the input scene whose optical flow is similar to the optical flow of the input video. Our intuition is supported by a user-study specifically designed to verify this statement. We have successfully tested our approach on several scenes and input videos, some of which are reported in the accompanying material of this paper
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