Ecology is the study of interactions and relationships between different organisms that live on earth. It can look at small micro organisms all the way up to large rainforest ecosystems. It encapsulates every natural entity found on the earth and is a crucial field of research when it comes to studying our rapidly changing climate. Over the past 50 years climate change has been a pressing issue for the humanity and its ecological impacts can be felt all across the world. myEcology is an artwork which places the subject (a person) as the host for an invasive parasite (the parasite resembles a pixelated mould). At that point the subject and the digital parasite enter an “ecological” relationship. The impact of that relationship can be explicitly felt and seen by the subject as a parasitic mould is grown over their image.
The amount of mould grown over the subject is based on the amount of carbon dioxide their home nation produces. Before running the software the user can determine which country they want to use. The data has been gathered from the European Commission’s 2018 report on nation’s carbon dioxide emissions. The software only focuses on the total amount of co2 released.
myEcology aims to put users in the position of earth. A picture of the user is generated but their body is covered in digital mould which distorts and ruins the image. It then asks users to consider what their environmental impact is on the earth and how can they limit the amount of “mould” they generate in the real world.
Image 1: shows object tracking, the red dot indicates the subject's average position
Image 2: shows the initial idea of "mould" growing on the subject (not influenced by data)
This project relies heavily on computer vision to create the artwork. The software uses frame differencing to separate the subject (the user) from the background and changes the background to a solid colour. This creates a green screen affect where the background and the subject can be interacted differently. The software also uses colour checking to locate where the centre of the subject is, this is the starting point for the mould to grow from (in the screenshots this is indicated by the red dot). The mould is grown using recursion and random walker algorithms, it also has checks to stop it from growing on the background.
Examples of Final Work
(Note: subjects are off centre in an attempt to avoid the webcams auto white-balancing, which breaks the software. Updated images will be uploaded once the correct camera becomes avaliable.)
The Coding Train, 11.5: Computer Vision: Color Tracking - Processing Tutorial, https://www.youtube.com/watch?v=nCVZHROb_dE
The Coding Train. 11.6: Computer Vision: Motion Detection - Processing Tutorial, https://www.youtube.com/watch?v=QLHMtE5XsMs_dE
Crippa, M., Oreggioni, G., Guizzardi, D., Muntean, M., Schaaf, E., Lo Vullo, E., Solazzo, E., Monforti-Ferrario, F., Olivier, J.G.J., Vignati, E., Fossil CO2 and GHG emissions of all world countries - 2019 Report, EUR 29849 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-11100-9, doi:10.2760/687800, JRC117610.