Dynamic and Interactive Scientific Posters: Visualising 3D Models and Simulation Data Using AR. / Payton, Ryan.

2020. Poster session presented at EGU General Assembly 2020, Vienna, Austria.

Research output: Contribution to conferencePoster

Unpublished

Abstract

Researchers often have to carefully select data for figures to best show their results for a static 2D format such as a conference poster or outreach handout. This can result in the scientific message being harder to understand or only part of the story being visualised. Augmented reality can help in improving the clarity of temporal data as well as the understanding of 3D structures which may be challenging to otherwise visualise.A series of software packages may be used in order to take video files (MP4, AVI etc…) and 3D model files (OBJ, STL, PLY etc…) and pair them with a target image, detectable by a mobile app for Android or iOS. The Vuforia engine plug-in for Unity allows for target images to be imported for use with AR and paired with a 3D model or video in Unity. Manipulation of the AR element is achieved using the Lean-Touch asset in Unity, allowing for scaling, rotation and movement.The incorporation of AR in science communication at a professional and public level creates a memorable interaction which is also enriched by greater scientific clarity. The interactive element of AR, especially using Lean-Touch, makes it an appealing tool for the public and children which results in greater engagement with science. The ability to show more data such as full simulations or experiment time lapses rather than a select series of still images also makes this an appealing tool for researchers in a variety of fields including modellers, experimentalists and anyone using digital data.
Original languageEnglish
DOIs
Publication statusUnpublished - May 2020
EventEGU General Assembly 2020 - Vienna, Austria
Duration: 4 May 20208 May 2020

Conference

ConferenceEGU General Assembly 2020
Abbreviated titleEGU2020
CountryAustria
CityVienna
Period4/05/208/05/20
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 39937219