Rendering Point Clouds with Compute Shaders

Schütz, Markus; Wimmer, Michael

doi:10.1145/3355056.3364554

Cited by 24 publications

(25 citation statements)

References 2 publications

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“…In this framework, the comparison between two models is done by means of integrated links. Another interesting open-source solution for rendering complex 3D scenarios is the framework that Potree developed by the Institute of Computer Graphics and Algorithms [42]. This tool, based on the WebGL technology, enables rendering point clouds through the use of an octree visualization system [42].…”

Section: D Visualization Methodologymentioning

confidence: 99%

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

Rodríguez‐Gonzálvez

Campo

Muñoz-Nieto

et al. 2019

IJGI

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Cultural heritage (CH) documentation is essential for the study and promotion of CH assets/sites, and provides a way of transmitting knowledge about heritage to future generations. The integration of the fourth dimension into geospatial datasets enables generating a diachronic model of CH elements, namely, a set of three-dimensional (3D) models to represent their evolution in various historical phases. The enhanced four-dimensional (4D) modeling (3D plus time) pursues a better understanding of the CH scenario, enriching historical hypotheses as well as contributing to the conservation and decision-making process. Although new geomatic techniques have reduced the amount of fieldwork, when put together, the geometric and temporal dimensions imply the interpretation of heterogeneous historical information sources and their integration. However, this situation could reach a critical point when the study elements are no longer present. The main challenge is to harmonize the different historical and archaeological data sources that are available with the current remains in order to graphically rebuild and model the lost CH assets with a high degree of reliability. Moreover, 4D web visualization is a great way to disclose the CH information and cultural identity. Additionally, it will serve as a basis to perform simulations of possible future risks or changes that can happen during planned or hypothetical restoration processes. This paper aims to examine the study case of a diachronic reconstruction by means of a mobile laser system (MLS) and reverse modeling techniques for a lost urban CH element: the citadel or Alcázar gate of Ávila. Within this aim, the final model is evaluated in terms of the consistency of the historical sources to assess its suitability considering the constructive interpretations that are required to integrate heterogenous data sources. Moreover, geometric modeling is evaluated regarding the current remains and its surroundings. Finally, a web 4D viewer is presented for its dissemination and publicity. This paper is an extended and improved version of our paper that was published in the 2018 ISPRS Technical Commission II Symposium, Riva del Garda, Italy, 3–7 June 2018.

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Section: D Visualization Methodologymentioning

confidence: 99%

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

Rodríguez‐Gonzálvez

Campo

Muñoz-Nieto

et al. 2019

IJGI

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“…The georeferencing accuracy, evaluated for each hyperspectral image by collecting 10 GCPs per scene, extracting their real-world coordinates from the pseudo-orthophoto and calculating a root mean square error (RMSE) in X, Y, and Z direction, is between 4 and 28 cm ( Table 7). The integrative 3D datasets can be viewed and evaluated under [109] in a browser (Chrome, Firefox, Safari on desktop PCs and mobile devices) online using the WebGL-based Potree viewer [110]. The viewer allows for rendering of the 3D datasets (SfM point cloud, and terrestrial VNIR-SWIR MWL, terrestrial LWIR LSU, UAV-based MWL hyperclouds), as well as measurements of distance, area, and height profiles.…”

Section: D Integrationmentioning

confidence: 99%

Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring

et al. 2018

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Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.

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“…External memory algorithms as a means to render arbitrary large 3D point clouds were initially introduced by Rusinkiewicz and Levoy (2000) and have since been adopted by numerous authors (Martinez-Rubi et al, 2016;Richter et al, 2015). Visual optimization techniques for 3D point clouds aim to reduce overdraw and underdraw alike, either preventing such visual artifacts by rendering points with an appropriate size and orientation (Schütz and Wimmer, 2015;Preiner et al, 2012) or eliminating them via image-based post-processing (Dobrev et al, 2010;Rosenthal and Linsen, 2008). While those approaches usually focus on non-immersive applications, Discher et al (2018a); Schütz (2016) discuss specific challenges and solutions regarding the visualization of 3D point clouds in VR environments.…”

Section: Related Workmentioning

confidence: 99%

“…To ensure an efficient subset retrieval, the data is hierarchically subdivided in a pre-processing step using spatial data structures such as octrees (Elseberg et al, 2013) or kd-trees (Goswami et al, 2013). In combination with web-based rendering concepts, these external memory algorithms allow the interactive inspection and visualization of arbitrary large 3D point clouds on a multitude of devices featuring vastly different CPU and GPU capabilities (Discher et al, 2018b;Schütz and Wimmer, 2015;Butler et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Interaction and Locomotion Techniques for the Exploration of Massive 3d Point Clouds in Vr Environments

Thiel

Discher

Richter

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Emerging virtual reality (VR) technology allows immersively exploring digital 3D content on standard consumer hardware. Using in-situ or remote sensing technology, such content can be automatically derived from real-world sites. External memory algorithms allow for the non-immersive exploration of the resulting 3D point clouds on a diverse set of devices with vastly different rendering capabilities. Applications for VR environments raise additional challenges for those algorithms as they are highly sensitive towards visual artifacts that are typical for point cloud depictions (i.e., overdraw and underdraw), while simultaneously requiring higher frame rates (i.e., around 90fps instead of 30&ndash;60fps). We present a rendering system for the immersive exploration and inspection of massive 3D point clouds on state-of-the-art VR devices. Based on a multi-pass rendering pipeline, we combine point-based and image-based rendering techniques to simultaneously improve the rendering performance and the visual quality. A set of interaction and locomotion techniques allows users to inspect a 3D point cloud in detail, for example by measuring distances and areas or by scaling and rotating visualized data sets. All rendering, interaction and locomotion techniques can be selected and configured dynamically, allowing to adapt the rendering system to different use cases. Tests on data sets with up to 2.6 billion points show the feasibility and scalability of our approach.

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Rendering Point Clouds with Compute Shaders

Cited by 24 publications

References 2 publications

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

Diachronic Reconstruction and Visualization of Lost Cultural Heritage Sites

Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring

Interaction and Locomotion Techniques for the Exploration of Massive 3d Point Clouds in Vr Environments

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