OMiCroN -- Oblique Multipass Hierarchy Creation while Navigating

Rendering large point clouds ordinarily requires building a hierarchical data structure for accessing the points that best represent the object for a given viewing frustum and level-of-detail. The building of such data structures frequently represents a large portion of the cost of the rendering pipeline both in terms of time and space complexity, especially when rendering is done for inspection purposes only. This problem has been addressed in the past by incremental construction approaches, but these either result in low quality hierarchies or in longer construction times. In this work we present OMiCroN -- Oblique Multipass Hierarchy Creation while Navigating -- which is the first algorithm capable of immediately displaying partial renders of the geometry, provided the cloud is made available sorted in Morton order. OMiCroN is fast, being capable of building the entire data structure in memory spending an amount of time that is comparable to that of just reading the cloud from disk. Thus, there is no need for storing an expensive hierarchy, nor for delaying the rendering until the whole hierarchy is read from disk. In fact, a pipeline coupling OMiCroN with an incremental sorting algorithm running in parallel can start rendering as soon as the first sorted prefix is produced, making this setup very convenient for streamed viewing.Comment: 13 pages, 15 figure

Towards Point-Based Acquisition and Rendering of Large Real-World Environments

This paper describes a pipeline for the acquisition and rendering of large real-world environments. In the acquisition phase, we use a laser rangefinder to capture the geometry of an environment, and a digital camera to capture its colors. In the rendering phase, we use a cluster of commodity PCs to render high-resolution images of the environment at interactive frame rates. In this paper, we describe in detail our scanning hardware, the tools we use to minimize the acquisition artifacts in the 3D scans, the procedure to register the scans to each other, and how to map colors from a photograph to a scan. We also present a sequential, out-of-core rendering approach that uses multiple threads to overlap rendering, visibility computation, and disk operations. Finally, we show how to use the sequential rendering approach as a building block for a parallel rendering system that uses a cluster of PCs to drive a high-resolution, multi-projector display wall. Our acquisition approach allows us to capture environments that would be extremely difficult to model by hand, and our rendering approach allows us to use inexpensive PCs, instead of high-end graphics workstations, to visualize those environments at interactive frame rates