Lukas Treyer

Visualizing Urban Anaylsis in Mixed Reality

This paper focuses on the computational creation of animated data visualization used to communicate urban analysis and design in a video. The goal is to combine abstract analysis information with concrete qualitative impressions of a location in the case study area of Zurich. Different urban analysis methods are used to procedurally create an animation with the open source software Blender that facilitates also the compositing process of animation with video. The resulting videos are created during an elective course at ETH Zurich. Anticipating the advent of augmented and mixed reality applications for daily life, we elaborate on their usability for urban design, education and collaborative planning with relatively easy to learn video effect methods. Not only different levels of abstraction are visualized but also -- inherent to the medium of video -- the relation to time.

Using a shifted lens to achieve visual depth in facade projections more efficiently

This paper describes a method for creating spatial illusion projections in a simple yet efficient way. It uses the horizontal and vertical lens shift properties of a virtual camera in a 3D modelling software to produce a normalized image that can be subsequently mapped with a traditional mapping technique, as cornerpin keystone correction for instance, onto a real facade. Our calculations describe how to automatically derive horizontal and vertical shift values. The method was developed during the creation process of a series of projections created with the 3D modelling software “Blender”.

Dynamic Multi-view, Multi-format, Multi-user Visualizations: For Future Cities

This paper introduces the concept of dynamic Multi-View, Multi-Format, Multi-User Visualizations. It also suggests aligning all visualization branches to a common problem, namely the design and implementation of future sustainable cities, such as Jakarta, Indonesia. While a lot of visualization research has extensively discussed the emotional, cognitive and coordinative benefits of visual representations, the application of such tools to solve grand societal problems has been neglected. We suggest focusing on Future Cities, since they require solutions and because the field seems to be ideal to align the various subgroups of visualization research. We derived this insight from about 1000 events in our physical value lab and our own software development - the Visual Manager and the Shuffler. The Visual Manager uses visual metaphors to illustrate risk assessment scenarios. The Shuffler is a framework to create coordinated multiple views. The innovative part of this framework is that different visual representations, complementary business logics and datasets can be distributed to different views, which calls for more transdisciplinary work in the design of dynamic multi-view, multi-format and multi-user software. This paper is relevant for researchers in all subgroups of visualization research - especially Knowledge Visualization and Information Visualization.

Value lab: Innovation in teaching visual design: There is nothing to wait for

In this paper we comment on design teaching and communication in the domain of architectural education, particularly in the initial parts of the design process, where hand sketching is applied. We are aware of advantages that electronic sketch devices incorporate, therefore we investigate their implementation in diverse phases of architectural studio education. We are testing our presumptions on site, running an experimental design studio with students at two universities: ETH Zurich and CVUT Prague. The focus lies in configuration and further use of Value Lab in teaching and in an adequate sketch application development. The tool is called ColLab sketch and its multi-interfacial manner fits large touch-tables as well as small tablets.

Machine learning approaches to understand the influence of urban environments on human’s physiological response

Abstract This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency unification, signal pairing, signal filtering, signal quantification, and data labeling. Furthermore, this paper contributes to human-environment interaction research, where a field study to understand the influence of environmental features such as varying sound level, illuminance, field-of-view, or environmental conditions on humans’ perception was proposed. In the study, participants of various demographic backgrounds walked through an urban environment in Zurich, Switzerland while wearing physiological and environmental sensors. Apart from signal processing, four machine learning techniques, classification, fuzzy rule-based inference, feature selection, and clustering, were applied to discover relevant patterns and relationship between the participants’ physiological responses and environmental conditions. The predictive models with high accuracies indicate that the change in the field-of-view corresponds to increased participant arousal. Among all features, the participants’ physiological responses were primarily affected by the change in environmental conditions and field-of-view.

Lightweight urban computation interchange (LUCI): a system to couple heterogeneous simulations and views

In this paper we introduce LUCI, a lightweight urban computation interchange system, designed to bring the advantages of calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases, that have been implemented to test and further develop our concepts and implementations.

Visualizing urban analysis in mixed reality

This paper focuses on the computational creation of animated data visualization used to communicate urban analysis and design in a video. The goal is to combine abstract analysis information with concrete qualitative impressions of a location in the case study area of Zurich. Different urban analysis methods are used to procedurally create an animation with the open source software Blender that facilitates also the compositing process of animation with video. The resulting videos are created during an elective course at ETH Zurich. Anticipating the advent of augmented and mixed reality applications for daily life, we elaborate on their usability for urban design, education and collaborative planning with relatively easy to learn video effect methods. Not only different levels of abstraction are visualized but also -- inherent to the medium of video -- the relation to time.