TY - JOUR A1 - Richter, Rico A1 - Döllner, Jürgen Roland Friedrich T1 - Concepts and techniques for integration, analysis and visualization of massive 3D point clouds JF - Computers, environment and urban systems N2 - Remote sensing methods, such as LiDAR and image-based photogrammetry, are established approaches for capturing the physical world. Professional and low-cost scanning devices are capable of generating dense 3D point clouds. Typically, these 3D point clouds are preprocessed by GIS and are then used as input data in a variety of applications such as urban planning, environmental monitoring, disaster management, and simulation. The availability of area-wide 3D point clouds will drastically increase in the future due to the availability of novel capturing methods (e.g., driver assistance systems) and low-cost scanning devices. Applications, systems, and workflows will therefore face large collections of redundant, up-to-date 3D point clouds and have to cope with massive amounts of data. Hence, approaches are required that will efficiently integrate, update, manage, analyze, and visualize 3D point clouds. In this paper, we define requirements for a system infrastructure that enables the integration of 3D point clouds from heterogeneous capturing devices and different timestamps. Change detection and update strategies for 3D point clouds are presented that reduce storage requirements and offer new insights for analysis purposes. We also present an approach that attributes 3D point clouds with semantic information (e.g., object class category information), which enables more effective data processing, analysis, and visualization. Out-of-core real-time rendering techniques then allow for an interactive exploration of the entire 3D point cloud and the corresponding analysis results. Web-based visualization services are utilized to make 3D point clouds available to a large community. The proposed concepts and techniques are designed to establish 3D point clouds as base datasets, as well as rendering primitives for analysis and visualization tasks, which allow operations to be performed directly on the point data. Finally, we evaluate the presented system, report on its applications, and discuss further research challenges. KW - 3D point clouds KW - System architecture KW - Classification KW - Out-of-core KW - Visualization Y1 - 2014 U6 - https://doi.org/10.1016/j.compenvurbsys.2013.07.004 SN - 0198-9715 SN - 1873-7587 VL - 45 SP - 114 EP - 124 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Discher, Sören A1 - Richter, Rico A1 - Döllner, Jürgen Roland Friedrich T1 - Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds JF - Advances in 3D Geoinformation N2 - 3D point clouds are a digital representation of our world and used in a variety of applications. They are captured with LiDAR or derived by image-matching approaches to get surface information of objects, e.g., indoor scenes, buildings, infrastructures, cities, and landscapes. We present novel interaction and visualization techniques for heterogeneous, time variant, and semantically rich 3D point clouds. Interactive and view-dependent see-through lenses are introduced as exploration tools to enhance recognition of objects, semantics, and temporal changes within 3D point cloud depictions. We also develop filtering and highlighting techniques that are used to dissolve occlusion to give context-specific insights. All techniques can be combined with an out-of-core real-time rendering system for massive 3D point clouds. We have evaluated the presented approach with 3D point clouds from different application domains. The results show the usability and how different visualization and exploration tasks can be improved for a variety of domain-specific applications. KW - 3D point clouds KW - LIDAR KW - Visualization KW - Point-based rendering Y1 - 2016 SN - 978-3-319-25691-7 SN - 978-3-319-25689-4 U6 - https://doi.org/10.1007/978-3-319-25691-7_3 SN - 1863-2246 SP - 49 EP - 62 PB - Springer CY - Cham ER - TY - JOUR A1 - Semmo, Amir A1 - Döllner, Jürgen Roland Friedrich T1 - Interactive image filtering for level-of-abstraction texturing of virtual 3D scenes JF - Computers & graphics : CAG ; an international journal of applications in computer graphics N2 - Texture mapping is a key technology in computer graphics. For the visual design of 3D scenes, in particular, effective texturing depends significantly on how important contents are expressed, e.g., by preserving global salient structures, and how their depiction is cognitively processed by the user in an application context. Edge-preserving image filtering is one key approach to address these concerns. Much research has focused on applying image filters in a post-process stage to generate artistically stylized depictions. However, these approaches generally do not preserve depth cues, which are important for the perception of 3D visualization (e.g., texture gradient). To this end, filtering is required that processes texture data coherently with respect to linear perspective and spatial relationships. In this work, we present an approach for texturing 3D scenes with perspective coherence by arbitrary image filters. We propose decoupled deferred texturing with (1) caching strategies to interactively perform image filtering prior to texture mapping and (2) for each mipmap level separately to enable a progressive level of abstraction, using (3) direct interaction interfaces to parameterize the visualization according to spatial, semantic, and thematic data. We demonstrate the potentials of our method by several applications using touch or natural language inputs to serve the different interests of users in specific information, including illustrative visualization, focus+context visualization, geometric detail removal, and semantic depth of field. The approach supports frame-to-frame coherence, order-independent transparency, multitexturing, and content-based filtering. In addition, it seamlessly integrates into real-time rendering pipelines and is extensible for custom interaction techniques. (C) 2015 Elsevier Ltd. All rights reserved. KW - Image filtering KW - Level of abstraction KW - Texturing KW - Virtual 3D scenes KW - Visualization KW - Interaction Y1 - 2015 U6 - https://doi.org/10.1016/j.cag.2015.02.001 SN - 0097-8493 SN - 1873-7684 VL - 52 SP - 181 EP - 198 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Laue, Ralf A1 - Awad, Ahmed Mahmoud Hany Aly T1 - Visual suggestions for improvements in business process diagrams JF - Journal of visual languages and computing N2 - Business processes are commonly modeled using a graphical modeling language. The most widespread notation for this purpose is business process diagrams in the Business Process Modeling Notation (BPMN). In this article, we use the visual query language BPMN-Q for expressing patterns that are related to possible problems in such business process diagrams. We discuss two classes of problems that can be found frequently in real-world models: sequence flow errors and model fragments that can make the model difficult to understand. By using a query processor, a business process modeler is able to identify possible errors in business process diagrams. Moreover, the erroneous parts of the business process diagram can be highlighted when an instance of an error pattern is found. This way, the modeler gets an easy-to-understand feedback in the visual modeling language he or she is familiar with. This is an advantage over current validation methods, which usually lack this kind of intuitive feedback. KW - Business process model KW - Business process diagram KW - BPMN-Q KW - Visualization Y1 - 2011 U6 - https://doi.org/10.1016/j.jvlc.2011.04.003 SN - 1045-926X VL - 22 IS - 5 SP - 385 EP - 399 PB - Elsevier CY - London ER -