TY - GEN A1 - Stojanovic, Vladeta A1 - Trapp, Matthias A1 - Richter, Rico A1 - Döllner, Jürgen Roland Friedrich T1 - A service-oriented approach for classifying 3D points clouds by example of office furniture classification T2 - Web3D 2018: Proceedings of the 23rd International ACM Conference on 3D Web Technology N2 - 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. KW - Indoor Models KW - 3D Point Clouds KW - Machine KW - Learning KW - BIM KW - Service-Oriented Y1 - 2018 SN - 978-1-4503-5800-2 U6 - https://doi.org/10.1145/3208806.3208810 SP - 1 EP - 9 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - Fricke, Andreas A1 - Döllner, Jürgen Roland Friedrich A1 - Asche, Hartmut T1 - Servicification - Trend or Paradigm Shift in Geospatial Data Processing? T2 - Computational Science and Its Applications – ICCSA 2018, PT III N2 - Currently we are witnessing profound changes in the geospatial domain. Driven by recent ICT developments, such as web services, serviceoriented computing or open-source software, an explosion of geodata and geospatial applications or rapidly growing communities of non-specialist users, the crucial issue is the provision and integration of geospatial intelligence in these rapidly changing, heterogeneous developments. This paper introduces the concept of Servicification into geospatial data processing. Its core idea is the provision of expertise through a flexible number of web-based software service modules. Selection and linkage of these services to user profiles, application tasks, data resources, or additional software allow for the compilation of flexible, time-sensitive geospatial data handling processes. Encapsulated in a string of discrete services, the approach presented here aims to provide non-specialist users with geospatial expertise required for the effective, professional solution of a defined application problem. Providing users with geospatial intelligence in the form of web-based, modular services, is a completely different approach to geospatial data processing. This novel concept puts geospatial intelligence, made available through services encapsulating rule bases and algorithms, in the centre and at the disposal of the users, regardless of their expertise. KW - Servicification KW - Geospatial intelligence KW - Spatial data handling systems Y1 - 2018 SN - 978-3-319-95168-3 SN - 978-3-319-95167-6 U6 - https://doi.org/10.1007/978-3-319-95168-3_23 SN - 0302-9743 SN - 1611-3349 VL - 10962 SP - 339 EP - 350 PB - Springer CY - Cham ER - TY - GEN A1 - Reimann, Max A1 - Klingbeil, Mandy A1 - Pasewaldt, Sebastian A1 - Semmo, Amir A1 - Trapp, Matthias A1 - Döllner, Jürgen Roland Friedrich ED - Sourin, A Sourina T1 - MaeSTrO: A Mobile App for Style Transfer Orchestration using Neural Networks T2 - International Conference on Cyberworlds (CW) N2 - 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. KW - non-photorealistic rendering KW - style transfer Y1 - 2018 SN - 978-1-5386-7315-7 U6 - https://doi.org/10.1109/CW.2018.00016 SP - 9 EP - 16 PB - IEEE CY - New York ER - TY - GEN A1 - Limberger, Daniel A1 - Gropler, Anne A1 - Buschmann, Stefan A1 - Döllner, Jürgen Roland Friedrich A1 - Wasty, Benjamin T1 - OpenLL BT - an API for Dynamic 2D and 3D Labeling T2 - 22nd International Conference Information Visualisation (IV) N2 - Today's rendering APIs lack robust functionality and capabilities for dynamic, real-time text rendering and labeling, which represent key requirements for 3D application design in many fields. As a consequence, most rendering systems are barely or not at all equipped with respective capabilities. This paper drafts the unified text rendering and labeling API OpenLL intended to complement common rendering APIs, frameworks, and transmission formats. For it, various uses of static and dynamic placement of labels are showcased and a text interaction technique is presented. Furthermore, API design constraints with respect to state-of-the-art text rendering techniques are discussed. This contribution is intended to initiate a community-driven specification of a free and open label library. KW - visualization KW - labeling KW - real-time rendering Y1 - 2018 SN - 978-1-5386-7202-0 U6 - https://doi.org/10.1109/iV.2018.00039 SP - 175 EP - 181 PB - IEEE CY - New York ER - TY - GEN A1 - Discher, Sören A1 - Richter, Rico A1 - Döllner, Jürgen Roland Friedrich ED - Spencer, SN T1 - A scalable webGL-based approach for visualizing massive 3D point clouds using semantics-dependent rendering techniques T2 - Web3D 2018: The 23rd International ACM Conference on 3D Web Technology N2 - 3D point cloud technology facilitates the automated and highly detailed digital acquisition of real-world environments such as assets, sites, cities, and countries; the acquired 3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. In this paper, we present a web-based system for the interactive and collaborative exploration and inspection of arbitrary large 3D point clouds. Our approach is based on standard WebGL on the client side and is able to render 3D point clouds with billions of points. It uses spatial data structures and level-of-detail representations to manage the 3D point cloud data and to deploy out-of-core and web-based rendering concepts. By providing functionality for both, thin-client and thick-client applications, the system scales for client devices that are vastly different in computing capabilities. Different 3D point-based rendering techniques and post-processing effects are provided to enable task-specific and data-specific filtering and highlighting, e.g., based on per-point surface categories or temporal information. A set of interaction techniques allows users to collaboratively work with the data, e.g., by measuring distances and areas, by annotating, or by selecting and extracting data subsets. Additional value is provided by the system's ability to display additional, context-providing geodata alongside 3D point clouds and to integrate task-specific processing and analysis operations. We have evaluated the presented techniques and the prototype system with different data sets from aerial, mobile, and terrestrial acquisition campaigns with up to 120 billion points to show their practicality and feasibility. KW - 3D Point Clouds KW - web-based rendering KW - point-based rendering Y1 - 2018 SN - 978-1-4503-5800-2 U6 - https://doi.org/10.1145/3208806.3208816 SP - 1 EP - 9 PB - Association for Computing Machinery CY - New York ER -