GPU Optimization of an Existing Free-Viewpoint Video System

Many video reconstruction systems seek to recreate a scene from captured video sequences but are unable to perform at interactive framerates. This project presents the optimization of such a system by utilizing a Graphics Processing Unit (GPU). The specialized nature of the GPU offers many challenges in non-traditional graphics pipelines, but can offer great performance benefits. This paper presents the process by which a next-generation GPU is utilized to accelerate the visual hull reconstruction and rendering in Cinematized Reality

GPU-Based Optimization of a Free-Viewpoint Video System

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering a is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality

Analysis of Game Interface Performance

This study tested the effects of different interfaces on players\u27 performance in racing games. Participants raced each other on three different configurations, a PC with a keyboard, a PC with a gamepad, and a PlayStation2 with a gamepad. Participants switched setups after each race. We found a slight advantage in performance, as measured by lap time, mean speed, and place, when using a gamepad over a keyboard. Learning, experience, and skill had a much larger effect than the interface

GPU-based optimization of a free-viewpoint video system

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality

GPU-Based Optimization of a Free-Viewpoint Video System

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering a is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality