GPU-BASED VOLUMETRIC RECONSTRUCTION OF TREES FROM MULTIPLE IMAGES

摘要

This paper presents a new hardware-accelerated approach on volumetric reconstruction of trees from images, based on the methods introduced by Reche Martinez et. al [Rec04]. The shown system applies an adapted CT procedure that uses a set of intensity images with known interior and exterior camera parameters for creating a 3D model of a tree, while requiring considerably less images then standard CT. At the same time, the paper introduces a GPU-based solution for the system. As tomographic reconstructions are rather complex tasks, the generation of high-resolution volumes can result in very time-consuming processess. While the performance of CPUs grew in compliance with Moore's law, GPU architectures showed a significant performance improvement in floating-point calculations. Regarding well parallelizeable processes, today's end-user graphics-cards can easily outperform high-end CPUs. By improving and modifying the existing methods of volumetric reconstruction in a way, that allows a parallelized implementation on graphics-hardware, a considerable acceleration of the computation times is realized. The paper gives an overview over the single steps from the acquisition of the oriented images displaying the tree till the realization of the final system on graphics processing hardware.