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Virtual 3D city models serve as an effective medium with manifold applications in geoinformation systems and services. To date, most 3D city models are visualized using photorealistic graphics. But an effective communication of geoinformation significantly depends on how important information is designed and cognitively processed in the given application context. One possibility to visually emphasize important information is based on non-photorealistic rendering, which comprehends artistic depiction styles and is characterized by its expressiveness and communication aspects. However, a direct application of non-photorealistic rendering techniques primarily results in monotonic visualization that lacks cartographic design aspects. In this work, we present concepts for cartography-oriented visualization of virtual 3D city models. These are based on coupling non-photorealistic rendering techniques and semantics-based information for a user, context, and media-dependent representation of thematic information. This work highlights challenges for cartography-oriented visualization of 3D geovirtual environments, presents stylization techniques and discusses their applications and ideas for a standardized visualization. In particular, the presented concepts enable a real-time and dynamic visualization of thematic geoinformation.
Virtual 3D city models play an important role in the communication of complex geospatial information in a growing number of applications, such as urban planning, navigation, tourist information, and disaster management. In general, homogeneous graphic styles are used for visualization. For instance, photorealism is suitable for detailed presentations, and non-photorealism or abstract stylization is used to facilitate guidance of a viewer's gaze to prioritized information. However, to adapt visualization to different contexts and contents and to support saliency-guided visualization based on user interaction or dynamically changing thematic information, a combination of different graphic styles is necessary. Design and implementation of such combined graphic styles pose a number of challenges, specifically from the perspective of real-time 3D visualization. In this paper, the authors present a concept and an implementation of a system that enables different presentation styles, their seamless integration within a single view, and parametrized transitions between them, which are defined according to tasks, camera view, and image resolution. The paper outlines potential usage scenarios and application fields together with a performance evaluation of the implementation.
This article presents multi-perspective 3D panoramas that focus on visualizing 3D geovirtual environments (3D GeoVEs) for navigation and exploration tasks. Their key element, a multi-perspective view (MPV), seamlessly combines what is seen from multiple viewpoints into a single image. This approach facilitates the presentation of information for virtual 3D city and landscape models, particularly by reducing occlusions, increasing screen-space utilization, and providing additional context within a single image. We complement MPVs with cartographic visualization techniques to stylize features according to their semantics and highlight important or prioritized information. When combined, both techniques constitute the core implementation of interactive, multi-perspective 3D panoramas. They offer a large number of effective means for visual communication of 3D spatial information, a high degree of customization with respect to cartographic design, and manifold applications in different domains. We discuss design decisions of 3D panoramas for the exploration of and navigation in 3D GeoVEs. We also discuss a preliminary user study that indicates that 3D panoramas are a promising approach for navigation systems using 3D GeoVEs.
Cartography-Oriented Design of 3D Geospatial Information Visualization - Overview and Techniques
(2015)
In economy, society and personal life map-based interactive geospatial visualization becomes a natural element of a growing number of applications and systems. The visualization of 3D geospatial information, however, raises the question how to represent the information in an effective way. Considerable research has been done in technology-driven directions in the fields of cartography and computer graphics (e.g., design principles, visualization techniques). Here, non-photorealistic rendering (NPR) represents a promising visualization category - situated between both fields - that offers a large number of degrees for the cartography-oriented visual design of complex 2D and 3D geospatial information for a given application context. Still today, however, specifications and techniques for mapping cartographic design principles to the state-of-the-art rendering pipeline of 3D computer graphics remain to be explored. This paper revisits cartographic design principles for 3D geospatial visualization and introduces an extended 3D semiotic model that complies with the general, interactive visualization pipeline. Based on this model, we propose NPR techniques to interactively synthesize cartographic renditions of basic feature types, such as terrain, water, and buildings. In particular, it includes a novel iconification concept to seamlessly interpolate between photorealistic and cartographic representations of 3D landmarks. Our work concludes with a discussion of open challenges in this field of research, including topics, such as user interaction and evaluation.
With increasing numbers of flights worldwide and a continuing rise in airport traffic, air-traffic management is faced with a number of challenges. These include monitoring, reporting, planning, and problem analysis of past and current air traffic, e.g., to identify hotspots, minimize delays, or to optimize sector assignments to air-traffic controllers. To cope with these challenges, cyber worlds can be used for interactive visual analysis and analytical reasoning based on aircraft trajectory data. However, with growing data size and complexity, visualization requires high computational efficiency to process that data within real-time constraints. This paper presents a technique for real-time animated visualization of massive trajectory data. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearance, and (3) real-time rendering within 3D virtual environments such as virtual 3D airport or 3D city models. Different visualization metaphors can be efficiently built upon this technique such as temporal focus+context, density maps, or overview+detail methods. As a general-purpose visualization technique, it can be applied to general 3D and 3+1D trajectory data, e.g., traffic movement data, geo-referenced networks, or spatio-temporal data, and it supports related visual analytics and data mining tasks within cyber worlds.
Mixed-projection treemaps
(2017)
This paper presents a novel technique for combining 2D and 2.5D treemaps using multi-perspective views to leverage the advantages of both treemap types. It enables a new form of overview+detail visualization for tree-structured data and contributes new concepts for real-time rendering of and interaction with treemaps. The technique operates by tilting the graphical elements representing inner nodes using affine transformations and animated state transitions. We explain how to mix orthogonal and perspective projections within a single treemap. Finally, we show application examples that benefit from the reduced interaction overhead.
The rapid digitalization of the Facility Management (FM) sector has increased the demand for mobile, interactive analytics approaches concerning the operational state of a building. These approaches provide the key to increasing stakeholder engagement associated with Operation and Maintenance (O&M) procedures of living and working areas, buildings, and other built environment spaces. We present a generic and fast approach to process and analyze given 3D point clouds of typical indoor office spaces to create corresponding up-to-date approximations of classified segments and object-based 3D models that can be used to analyze, record and highlight changes of spatial configurations. The approach is based on machine-learning methods used to classify the scanned 3D point cloud data using 2D images. This approach can be used to primarily track changes of objects over time for comparison, allowing for routine classification, and presentation of results used for decision making. We specifically focus on classification, segmentation, and reconstruction of multiple different object types in a 3D point-cloud scene. We present our current research and describe the implementation of these technologies as a web-based application using a services-oriented methodology.
Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expression, the technology still faces inherent limitations in providing low-level controls for localized image stylization. This work enhances state-of-the-art neural style transfer techniques by a generalized user interface with interactive tools to facilitate a creative and localized editing process. Thereby, we first propose a problem characterization representing trade-offs between visual quality, run-time performance, and user control. We then present MaeSTrO, a mobile app for orchestration of neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors. At this, first user tests indicate different levels of satisfaction for the implemented techniques and interaction design.
Thematic maps are a common tool to visualize semantic data with a spatial reference. Combining thematic data with a geometric representation of their natural reference frame aids the viewer’s ability in gaining an overview, as well as perceiving patterns with respect to location; however, as the amount of data for visualization continues to increase, problems such as information overload and visual clutter impede perception, requiring data aggregation and level-of-detail visualization techniques. While existing aggregation techniques for thematic data operate in a 2D reference frame (i.e., map), we present two aggregation techniques for 3D spatial and spatiotemporal data mapped onto virtual city models that hierarchically aggregate thematic data in real time during rendering to support on-the-fly and on-demand level-of-detail generation. An object-based technique performs aggregation based on scene-specific objects and their hierarchy to facilitate per-object analysis, while the scene-based technique aggregates data solely based on spatial locations, thus supporting visual analysis of data with arbitrary reference geometry. Both techniques can apply different aggregation functions (mean, minimum, and maximum) for ordinal, interval, and ratio-scaled data and can be easily extended with additional functions. Our implementation utilizes the programmable graphics pipeline and requires suitably encoded data, i.e., textures or vertex attributes. We demonstrate the application of both techniques using real-world datasets, including solar potential analyses and the propagation of pressure waves in a virtual city model.
The use of Building Information Modeling (BIM) for Facility Management (FM) in the Operation and Maintenance (O&M) stages of the building life-cycle is intended to bridge the gap between operations and digital data, but lacks the functionality of assessing the state of the built environment due to non-automated generation of associated semantics. 3D point clouds can be used to capture the physical state of the built environment, but also lack these associated semantics. A prototypical implementation of a service-oriented architecture for classification of indoor point cloud scenes of office environments is presented, using multiview classification. The multiview classification approach is tested using a retrained Convolutional Neural Network (CNN) model - Inception V3. The presented approach for classifying common office furniture objects (chairs, sofas and desks), contained in 3D point cloud scans, is tested and evaluated. The results show that the presented approach can classify common office furniture up to an acceptable degree of accuracy, and is suitable for quick and robust semantics approximation - based on RGB (red, green and blue color channel) cubemap images of the octree partitioned areas of the 3D point cloud scan. Additional methods for web-based 3D visualization, editing and annotation of point clouds are also discussed. Using the described approach, captured scans of indoor environments can be semantically enriched using object annotations derived from multiview classification results. Furthermore, the presented approach is suited for semantic enrichment of lower resolution indoor point clouds acquired using commodity mobile devices.