The aim of this thesis is non-realistic video rendering. It starts with a summary of existing techniques and then this thesis concentrates on selected methods that are able to work in real-time. To process video more effectivelly, we use accelleration on graphical processing unit with usage of OpenGL and GLSL.

Generating fully 3D terrains is a dificult task, meaning that we need to store a lot of data or do a lot of computing or both. We can reduce or completly eliminate the data srorage by using a procedural approch, but this is where the problem gets realy computationaly costly and the CUDA platform comes in. CUDA kernels runinng parallely on graphic accelerators can rapidly decrease time needed for computation, allowing even these complex calculations to work in real time or even better. Finding its use in game or movie industry.

The aim of the master's thesis is to create a graphic intro with the limited size of 64kB. Brief history of a demoscene and the graphics library OpenGL is introduced in the following text. The main part of the work is a description of minimal graphics techniques used in a creative process and their further application in the final programme.

This thesis presents optimization techniques for efficient rendering of complex scenes on mobile devices. The introductory part of the text describes Unity game engine and the topic of mobile game development using this tool. Then follows a presentation of important optimization principles and methods for terrain rendering, large scale rendering of animated objects, rendering of animated water surfaces and of other elements in the scenes. The described methods include both general principles of optimization and specific optimization approaches based on the features of Unity game engine. The implementation of presented methods is described and used in practice in the context of mobile strategy game development.

This thesis focuses on 3D computer graphics and the continuous maximisation of rendering quality and performance. Its main focus is the critical analysis of numerous real-time rendering algorithms and the construction of an empirically derived system for the high-speed rendering of shader-based special effects, lighting effects, shadows, reflection and refraction, post-processing effects and the processing of physics. This critical analysis allows us to assess the relationship between rendering quality and performance. It also allows for the isolation of key algorithmic weaknesses and possible bottleneck areas. Using this performance data, gathered during the analysis of various rendering algorithms, we are able to define a selection engine to control the real-time cycling of rendering algorithms and special effects groupings based on environmental conditions. Furthermore, as a proof of concept, to balance Central Processing Unit (CPU) and Graphic Processing Unit (GPU) load for and increased speed of execution, our selection system unifies the GPU and CPU as a single computational unit for physics processing and environmental mapping. This parallel computing system enables the CPU to process cube mapping computations while the GPU can be tasked with calculations traditionally handled solely by the CPU. All analysed and benchmarked algorithms were implemented as part of a modular rendering engine. This engine offers conventional first-person perspective input control, mesh loading and support for shader model 4.0 shaders (via Microsoft’s High Level Shader Language) for effects such as high dynamic range rendering (HDR), dynamic ambient lighting, volumetric fog, specular reflections, reflective and refractive water, realistic physics, particle effects, etc. The test engine also supports the dynamic placement, movement and elimination of light sources, meshes and spatial geometry. Critical analysis was performed via scripted camera movement and object and light source additions – done not only to ensure consistent testing, but also to ease future validation and replication of results. This provided us with a scalable interactive testing environment as well as a complete solution for the rendering of computationally intensive 3D environments. As a full-fledged game engine, our rendering engine is amenable to first- and third-person shooter games, role playing games and 3D immersive environments. Evaluation criteria (identified to access the relationship between rendering quality and performance), as mentioned, allows us to effectively cycle algorithms based on empirical results and to distribute specific processing (cube mapping and physics processing) between the CPU and GPU, a unification that ensures the following: nearby effects are always of high-quality (where computational resources are available), distant effects are, under certain conditions, rendered at a lower quality and the frames per second rendering performance is always maximised. The implication of our work is clear: unifying the CPU and GPU and dynamically cycling through the most appropriate algorithms based on ever-changing environmental conditions allow for maximised rendering quality and performance and shows that it is possible to render high-quality visual effects with realism, without overburdening scarce computational resources. Immersive rendering approaches used in conjunction with AI subsystems, game networking and logic, physics processing and other special effects (such as post-processing shader effects) are immensely processor intensive and can only be successfully implemented on high-end hardware. Only by cycling and distributing algorithms based on environmental conditions and through the exploitation of algorithmic strengths can high-quality real-time special effects and highly accurate calculations become as common as texture mapping. Furthermore, in a gaming context, players often spend an inordinate amount of time fine-tuning their graphics settings to achieve the perfect balance between rendering quality and frames-per-second performance. Using this system, however, ensures that performance vs. quality is always optimised, not only for the game as a whole but also for the current scene being rendered – some scenes might, for example, require more computational power than others, resulting in noticeable slowdowns, slowdowns not experienced thanks to our system’s dynamic cycling of rendering algorithms and its proof of concept unification of the CPU and GPU. / Thesis (PhD)--University of Pretoria, 2012. / Computer Science / unrestricted