Interactive 3D scene modeling and visualization system

Author(s):  
Roman Grebinnik ◽  
Alexander Lipanov
2020 ◽  
Vol 39 (7) ◽  
pp. 57-68
Author(s):  
Tomer Weiss ◽  
Ilkay Yildiz ◽  
Nitin Agarwal ◽  
Esra Ataer‐Cansizoglu ◽  
Jae‐Woo Choi

2019 ◽  
Vol 2019 (7) ◽  
pp. 465-1-465-7
Author(s):  
Sjors van Riel ◽  
Dennis van de Wouw ◽  
Peter de With

2018 ◽  
pp. 31-63 ◽  
Author(s):  
Lukáš Herman ◽  
Tomáš Řezník ◽  
Zdeněk Stachoň ◽  
Jan Russnák

Various widely available applications such as Google Earth have made interactive 3D visualizations of spatial data popular. While several studies have focused on how users perform when interacting with these with 3D visualizations, it has not been common to record their virtual movements in 3D environments or interactions with 3D maps. We therefore created and tested a new web-based research tool: a 3D Movement and Interaction Recorder (3DmoveR). Its design incorporates findings from the latest 3D visualization research, and is built upon an iterative requirements analysis. It is implemented using open web technologies such as PHP, JavaScript, and the X3DOM library. The main goal of the tool is to record camera position and orientation during a user’s movement within a virtual 3D scene, together with other aspects of their interaction. After building the tool, we performed an experiment to demonstrate its capabilities. This experiment revealed differences between laypersons and experts (cartographers) when working with interactive 3D maps. For example, experts achieved higher numbers of correct answers in some tasks, had shorter response times, followed shorter virtual trajectories, and moved through the environment more smoothly. Interaction-based clustering as well as other ways of visualizing and qualitatively analyzing user interaction were explored.


Author(s):  
Daniel G. Aliaga ◽  
Ji Zhang ◽  
Mireille Boutin
Keyword(s):  

2020 ◽  
Vol 226 ◽  
pp. 03011
Author(s):  
Maria Grigorieva ◽  
Mikhail Titov ◽  
Timofei Galkin ◽  
Igal Milman

The Interactive Visual Explorer (InVEx) application is designed as a visual analytics tool for Big Data analysis. Visual analytics is an integral approach to data analysis, combining methods of intellectual data analysis with advanced interactive visualization. One of the main objectives of InVExis to process large data samples by decreasing their level of detail (LoD).The proposed approach includes clustering as well as flexible grouping by different parameters, providing the exploration of data from the lowest to the highest level of details. The results of grouping and clusterization arevisualized using interactive 3D scene and parallel coordinates, allowing the user to gain insight into data, to explore hidden correlations and trends of parameters.


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