@inbook{16406, abstract = {{In order to evaluate the efficiency of algorithms for real-time 3D rendering, different properties like rendering time, occluded triangles, or image quality, need to be investigated. Since these properties depend on the position of the camera, usually some camera path is chosen, along which the measurements are performed. As those measurements cover only a small part of the scene, this approach hardly allows drawing conclusions regarding the algorithm's properties at arbitrary positions in the scene. The presented method allows the systematic and position-independent evaluation of rendering algorithms. It uses an adaptive sampling approach to approximate the distribution of a property (like rendering time) for all positions in the scene. This approximation can be visualized to produce an intuitive impression of the algorithm's behavior or be statistically analyzed for objectively rating and comparing algorithms. We demonstrate our method by evaluating performance aspects of a known occlusion culling algorithm. }}, author = {{Jähn, Claudius and Eikel, Benjamin and Fischer, Matthias and Petring, Ralf and Meyer auf der Heide, Friedhelm}}, booktitle = {{Advances in Visual Computing}}, isbn = {{9783642419133}}, issn = {{0302-9743}}, title = {{{Evaluation of Rendering Algorithms Using Position-Dependent Scene Properties}}}, doi = {{10.1007/978-3-642-41914-0_12}}, year = {{2013}}, } @inbook{16407, abstract = {{Many virtual 3D scenes, especially those that are large, are not structured evenly. For such heterogeneous data, there is no single algorithm that is able to render every scene type at each position fast and with the same high image quality. For a small set of scenes, this situation can be improved if different rendering algorithms are manually assigned to particular parts of the scene by an experienced user. We introduce the Multi-Algorithm-Rendering method. It automatically deploys different rendering algorithms simultaneously for a broad range of scene types. The method divides the scene into subregions and measures the behavior of different algorithms for each region in a preprocessing step. During runtime, this data is utilized to compute an estimate for the quality and running time of the available rendering algorithms from the observer's point of view. By solving an optimizing problem, the image quality can be optimized by an assignment of algorithms to regions while keeping the frame rate almost constant. }}, author = {{Petring, Ralf and Eikel, Benjamin and Jähn, Claudius and Fischer, Matthias and Meyer auf der Heide, Friedhelm}}, booktitle = {{Advances in Visual Computing}}, isbn = {{9783642419133}}, issn = {{0302-9743}}, title = {{{Real-Time 3D Rendering of Heterogeneous Scenes}}}, doi = {{10.1007/978-3-642-41914-0_44}}, year = {{2013}}, }