This thesis presents a novel technique in computer graphics to simulate realtime
global illumination using path tracing. Path tracing is done with compute shaders on the graphics card (GPU) to perform rendering in a highly parallelized manner. To improve the overall performance of tracing rays, the Line Space is used as an acceleration data structure in different variations, resulting in better
empty space skipping. The Line Space saves scene information based on a previous voxelization in direction-dependent shafts and is generated and traversed on the GPU. With this procedure, indirect lighting and soft shadows can be computed in a physically correct way. Furthermore, using the Line Space, path tracing can be performed mostly independent of the complexity of the scene geometry with over 100 frames per second, which is truly real-time and much faster than using a comparable voxel grid. The image quality is not affected negatively by this technique and the shadow quality is in most cases much better compared to shadow-mapping.
This thesis presents two methods for the computation of global illumination. The first is an extension of Reflective Shadow Maps with an additional shadow test in order to handle occlusion. The second method is a novel, bidirectional Light-Injection approach. Rays originating from the light source are traced through the scene and stored inside the shafts of the Linespace datastructure. These shafts are a discretization of the possible spatial directions. The Linespaces are embedded in a Uniform Grid. When retrieving this pre-calculated lightning information no traversal of datastructures and no additional indirection is necessary in the best-case scenario. This reduces computation time and variance compared to Pathtracing. Areas that are mostly lit indirectly and glas profit the most from this. However, the result is only approximative in nature and produces visible artifacts.
This bachelor thesis deals with the comparison related to the similarity of recorded WiFi patterns during the tracing of a path through the streets of a large city. Both MAC address only comparison has been investigated as well as the incorporation of RSSI values, whereby the localization accuracy has been evaluated. Methods for the detection of different types and combinations of loops in the path are demonstrated likewise the attempt to estimate the degree of urban development in the environment of the user by assessing the received signal strength and signal-to-noise ratio of GPS satellites and GSM cell towers.
In order to observe a user- proximity to a certain spot on a large public square the absorption of WiFi signals by the human body has been taken into account. Finally, the results of a comparison of the computing performance of a modern smartphone versus the alternative of remote calculation on a server including data transmission via cellular data network are presented.