D01 | Perception-Guided Adaptive Modeling of 3D Virtual Cities Based on Probabilistic Grammars
The goal of the project is to create quantitative methods for the perception-aware representation of 3D virtual cities. We will develop a grammar-based system for the effective visual communication of building-related information via geometric 3D building representations that induce a defined degree of perceptual insight in the observer’s mind. The system will allow us to quantify the perceptual insight and predict the effects of modified system parameters. Moreover, it will be possible to enhance the perceptual insight by specifically changing the geometric representation.
Research Questions
Which geometric 3D representation is, given a context, best suited to enable a maximum understanding of the information that is intended to be transmitted?
Which aspects or properties of geometric 3D building representations are relevant for the perception of building-related semantic information?
How can we formalize and use this knowledge to develop a perception-aware modeling concept?
How can we quantify the quality of 3D building representations in a way that fits the viewer’s perception?
Fig. 1: Grammar-based 3D city model of Stuttgart.
Publications
Project Group A
Models and Measures
Completed
Project Group B
Adaptive Algorithms
Completed
Project Group C
Interaction
Completed
Project Group D
Applications
Completed
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© SFB-TRR 161 | Quantitative Methods for Visual Computing | 2019.