Aboriginal Art

Budyari yaguna, Señor William Dawes.  In my Australian adventure, I not only came across media about creativity but also creative media, especially of the aboriginal variety. Before getting to that, however, let me give a shout out to the Bhullar brothers, about whom a viral campaign we never did start, for getting a toehold in the NBA.

On the first day of the trip, we saw a traditional aboriginal didgeridoo and dance performance at Currumbin in Queensland. Later in the trip, we saw the aboriginal-inspired contemporary dance production Patyegarang at the Sydney Opera House.  Didgeridoo street performers greeted us at Circular Quay before we made our way by ferry to Manly.

Some of the beach-front galleries there were of aboriginal art.  I was especially drawn to the works of Tarisse King including her Earth Images. The dot paintings are mesmerizing in a unique way.  They are meant to represent a view of the earth from above.

Upon looking at her paintings, I wondered to myself whether something similar could be created using Gaussian processes and morphological image processing.  Here is my attempt at computer art via the following Matlab script:

seed = 1234; %random seed
n = 50; %grid size
r = 10; %repititions per point
s = 8; %resize scale for skeleton
l = 0.05; %squared exponential kernel parameter

rng(seed);

%create a grid
[X1,X2] = meshgrid(linspace(0,1,n),linspace(0,1,n));
x = [X1(:),X2(:)];

%covariance calculation using squared exponential kernel
K = exp(-squareform(pdist(x).^2/(2*l^2)));
[V,D]=eig(K);
A=V*(D.^(1/2));

%sample from Gaussian process
gaussian_process_sample = A*randn(n^2,1);

%calculate skeleton of the peaks
skeleton = bwmorph(imresize(reshape(real(gaussian_process_sample),n,n),s)>0,'skel',Inf);

%plot the painting on a black background using randomly perturbed copies of points from the Gaussian process sample and overlay the skeleton
figure; hold on;
scatter(repmat(x(:,1),r,1)+randn(r*n^2,1)/100,repmat(x(:,2),r,1)+randn(r*n^2,1)/100,12,repmat(gaussian_process_sample,r,1)+randn(r*n^2,1)/50,'filled');
h = imshow(cat(3,ones(n*s,n*s),ones(n*s,n*s),0.8*ones(n*s,n*s)),'XData',linspace(0,1,n*s),'YData',linspace(0,1,n*s));
set(h,'AlphaData',skeleton);
axis on; axis image; whitebg(gcf,'k'); set(gca,'XTick',[],'YTick',[],'box','on');
colormap([[linspace(0.04,1,24).';ones(40,1)],[zeros(24,1);linspace(0,0.84,40).'],zeros(64,1)]);

seed = 1234

seed = 1235

seed = 1236

What do you think?

Random Episodic Silent Thought

G’day mate.  I had a very nice time in Australia and our olfaction stuff was well received at the SSP Workshop.  While I was away, the computational creativity stuff debuted in its Chef Watson manifestation, but that was only one of many creativity-related things I came across during my trip.

On the flight back, I watched The Lego Movie, which in addition to featuring a 1980-Something Space Guy like we used to play with at the Mehrotra residence, is a commentary on the value of creativity.  I hadn’t realized beforehand that the movie’s theme was the supremacy of creatively building things over only following the instructions.  I’m glad I watched it.

I came across articles about creativity in The Atlantic and the New York Times Bits Blog.

Another pleasant viewing experience on the flight was the Australian Broadcasting Corporation’s documentary miniseries Redesign My Brain with Todd Sampson.  It helped me understand how several parts of your research flow together.  The first part of the miniseries utilizes the concept of neuroplasticity to show how Lumosity-like exercises can improve brain function along three dimensions: speed of thought, attention, and memory. I think the first of these can be related to typical Shannon theory, the second to some of your new information theory stuff incorporating Bayesian surprise, and the third to your new associative memory stuff.  The second part of the miniseries is all about human creativity starting with divergent thinking and then moving on to four criteria for creativity: effectiveness, novelty, elegance, and genesis.  The divergent thinking, effectiveness, and novelty are very much part of the computational creativity process we espoused, the Chef Watson app is elegant, and the extension to fashion, business processes, etc. that you talk about is the genesis. 

The last part of the creativity episode is about lateral thinking.  I wonder if and how you can investigate or model lateral thinking using information theory and statistical signal processing, and whether you’d want to include it in your research agenda.