AR-Media is one of the quickest ways to get started in Augmented Reality. The system is free for non commercial use and offers plugins for 3D Max, SketchUp and others with players running on iOS/Android and desktop devices via a webcam. The plugin used to be £100 + but the move to enhanced functionality and free for non commercial use makes it the first place to explore AR.
AR Virtual Projector on iOS
The plugin not only allows us of 3D models and animations but also movies and audio – the clip below demonstrates two example models we have built using AR Media, visualised using the AR Media player on iOS with models uploaded via DropBox:
Mixing AR Tags with 3D Max, CityEngine and Lumion opens up a lot of possibilites for rapid visualisation - head over to AR Media to download the various plugins required.
CASA Working Paper 190 – Visualising Spatial and Social Media (pdf)
In this working paper we begin by surveying the development of computer graphics as it has influenced the development of the spatial representation of social and economic data, charting the history of computer cartography and geographic information systems (GIS) which have broadened into a wide array of forms for scientific visualisation. With the advent of the World Wide Web and the widespread adoption of graphical user interfaces (GUIs) to most kinds of computer device, visualisation has become central to most sciences and to the dissemination of many kinds of data and information. We divide our treatment of this domain according to three themes.
First we examine how the 2-dimensional map has become key to many kinds of spatial representation, showing how this software has moved from the desktop to the web as well as how 2-d has moved to 3-d in terms of the visualisation of maps.
Second, we explore how social data is being augmented by space-time series generated in real time and show how such real-time streaming of data presents problems and opportunities in which visualisation is key. We illustrate these new data for basic feeds from cities but then move to examine data from transit systems, social media, and data that is pulled from the crowd – crowdsourcing.
Finally we note the development of visual analytics showing how 2-d and 3-d spatial representations are essential to interpreting the outputs and the workings of more complex models and simulations.We conclude with the notion that much of what we develop in this chapter for the space-time domain is generic to the future representation of all kinds of social data.