Radim Dvorak

Real-time Terrain Deformations

This paper presents a method for a physically based real-time terrain deformation. The motivation originates from the fact that there exist many deformable models, but the terrain deformation is a special problem in the field of computer graphics. OpenSceneGraph toolkit provides an excellent environment for the large terrain visualization and it was accepted as a standard for many graphic specialists. Therefore, the main goal of this method is the local deformation ability of some large terrain, which is represented by a sub-graph of OpenSceneGraph scene. However, the technique may be easily adaptable to any terrain representation. The results show a great potential of the used method and thus there is outlined the future work at the end.

Towards Accelerated Computation of Atmospheric Equations Using CUDA

Main objective of this paper is to outline possibleways how to achieve a substantial acceleration in caseof advection-diffusion equation (A-DE) calculation,which is commonly used for a description of thepollutant behavior in atmosphere. A-DE is a kind ofpartial differential equation (PDE) and in general caseit is usually solved by numerical integration due to itshigh complexity. These types of calculations are timeconsuming thus the main idea of our work is to adoptCUDA platform and commodity GPU card to do thecalculations in a faster way. The solution is based onmethod of lines with 4th order Runge-Kutta scheme tohandle the integration. As a matter of fact, the selectedapproach involves number of auxiliary variables andthus the memory management is critical in order toachieve desired performance. We have implementedseveral possible solutions that use different memoryaccess schemes. Detailed evaluation is provided in thispaper where the obtained results show a tremendousprocessing speed up in comparison to CPU.

Inspired by Bertillon - Recognition based on anatomical features from 3D face scans

We present an automatic 3D face recognition algorithm that is inspired by Alphonse Bertillons anthropometry. Our recognition pipeline consists of several steps. First, the facial landmarks such as the tip of the nose or the inner eye corners are detected. Subsequently the head rotation is compensated during the orientation normalization process. The facial features are extracted by performing 61 different measures. We also present a feature evaluation function that rates individual components of the feature vector. Finally, our results are compared with two other 3D face recognition methods. We show that the multi-algorithmic system consisting of the anatomical-based recognition together with the eigenfaces method and the recognition using histogram-based features reaches significantly better results than any of the employed methods individually.

GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Main objective of this paper is to outline possible ways how to achieve a substantial acceleration in case of advection-diffusion equation (A-DE) calculation, which is commonly used for a description of the pollutant behavior in atmosphere. A-DE is a kind of partial differential equation (PDE) and in general case it is usually solved by numerical integration due to its high complexity. These types of calculations are time consuming thus the main idea of our work is to adopt compute unified device architecture (CUDA) software framework and commodity add-on card with generalpurpose graphics processing unit (GPU) to do the calculations in a faster way. The solution is based on method of lines with 4 th order Runge-Kutta scheme to handle the integration. As a matter of fact, the selected approach involves number of auxiliary variables and thus the memory management is critical in order to achieve desired performance. From a technical point of view, we have implemented a particular variant of the A-DE system, where the pollutant concentration is time-dependent. An efficient data handling is primarily based on the exploitation of shared memory blocks and texture caches inside GPU chip. Detailed evaluation of the obtained results is given in this paper where an astonishing execution speed up of GPU-based solution is demonstrated in comparison to standard CPU.

Object Surface Reconstruction from One Camera System

In this paper, there is introduced an approach to surface reconstruction of an object captured by one grayscale camera with a small resolution. The proposed solution expects a rectangular grid being projected onto the object and the camera capturing the situation from position different to the grid projector position. The crucial part of the method is exact detection of the grid. The structure of the grid is identified by the centers of the inner space between its lines. The reconstruction process itself is based on a simple math of perspective projection of the captured image. Due to the small resolution of the image some errors arise during object surface reconstruction. We proposed a correction of the calculated coordinates, which is a simple one-dimensional function depending on the distance from the camera. The method performs very well as the results in conjunction with the precision evaluation indicate at the end of the paper.

Modeling of Atmospheric Dispersion from Point Source

This paper deals with numerical approach to modeling of atmospheric dispersion of pollutant caused by a point source. The modeling of a pollution in the atmosphere has a long history and has gone throw great improvements over the last century. Two main methods can be distinguished from the modeling point of view: the analytical and the numerical methods. Both methods have their advantages and disadvantages, however, in the latest developments the numerical method has had the major role. Our work has been concerned on modeling pollution in the atmosphere caused by small sources. These sources can be marked as point sources. For the primary validation of our numerical solution, we have used a simple version of the model. The analytical solution of this version can be obtained and may be used for comparison. An intended progress of our work is outlined at the end of the paper.

3D face recognition utilizing a low-cost depth sensor

This demo shows a working prototype of the 3D face recognition biometric device utilizing a low-cost depth sensor, namely SoftKinetic DS325. It is based on the Intel Celeron board for embedded PCs, the sensor, and a touch screen.

3D and Thermo-Face Fusion

Most biometric-based systems use a combination of various biometrics to improve reliability of decision. These systems are called multi-modal biometric systems. For example, they can include video, infrared, and audio data for identification of appearance (encompassing natu‐ ral changes such as aging, and intentional ones, such as surgical changes), physiological characteristics (temperature, blood flow rate), and behavioral features (voice and gait) [1].

Scanning and Measuring Device for Diagnostic of Barrel Bore

The article discusses the design, mechanical design, electronics and software for robot diagnosis of barrels with caliber of 120 mm to 155 mm. This diagnostic device is intended primarily for experimental research and verification of appropriate methods and technologies for the diagnosis of the main bore guns. Article also discusses the design of sensors and software, the issue of data processing and image reconstruction obtained by scanning of the surface of the bore.