QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets

We introduce QuadStack, a novel algorithm for volumetric data compression and direct rendering. Our algorithm exploits the data redundancy often found in layered datasets which are common in science and engineering fields such as geology, biology, mechanical engineering, medicine, etc. QuadStack first compresses the volumetric data into vertical stacks which are then compressed into a quadtree that identifies and represents the layered structures at the internal nodes. The associated data (color, material, density, etc.) and shape of these layer structures are decoupled and encoded independently, leading to high compression rates (4× to 54× of the original voxel model memory footprint in our experiments). We also introduce an algorithm for value retrieving from the QuadStack representation and we show that the access has logarithmic complexity. Because of the fast access, QuadStack is suitable for efficient data representation and direct rendering. We show that our GPU implementation performs comparably in speed with the state-of-the-art algorithms (18-79 MRays/s in our implementation), while maintaining a significantly smaller memory footprint

Global Visibility

Solving the hidden surface removal is an essential problem since the early time of computer graphics. Most of the algorithms designed, like z-buffer or BSP-tree, are not output-sensitive what means, that their time complexity is proportional to the total number of graphic primitives in the model. However, in many complex models most their parts are invisible to an observer while located in certain region. This observation yields a search to design output-sensitive algorithms with the runtime complexity (time of rendering) proportional to the number of visible graphic primitives. We present one such algorithm together withe an empirical evidence of the asset of the visibility determination. The method presented in this paper subdivides the model into smaller parts (cells) continuing with determination of visibility relations between them. To describe potentially visible sets a tree data structure is used, where edges correspond to tight approximations of potentially visible frustrums. K..

Ray Tracing with Rope Trees

In this paper an acceleration method for finding the nearest ray--object intersection for ray tracing purposes is presented. We use the concept of BSP trees enriched by rope trees. These are used to accelerate the traversal of the BSP tree. We give a comparison of experimental results between the technique based on BSP tree and uniform spatial subdivision. Key words: spatial subdivision, BSP tree, spatial data structures, rope trees, ray tracing. 1 Introduction Ray tracing is a well--known rendering technique for producing realistic images that simulates well specular surfaces. The main drawback of this algorithm is its rather big computational complexity, that disallows its interactive use. The problem has been focused a great deal of research interest in the past leading to some practical techniques to accelerate the basic algorithm. The principal expense of ray tracing is the determination of the closest ray--object intersection for a given ray and a set of objects. This problem i..