Photo Rendering with Swarms: From Figurative to Abstract Pherogenic Imaging

Carlos M. Fernandes, Antonio M. Mora, J.J. Merelo (University of Granada) C. Cotta (University of Malaga)

A.C. Rosa (Technical University of Lisbon)

2013 IEEE Symposium Series on Computational Intelligence

}  KANTS is swarm intelligence clustering algorithm.

}  Uses stigmergy – communication with and via the environment – as the basic rule.

}  Data samples are the swarm. They communicate and self-organize into clusters of similar samples.

2013 IEEE Symposium Series on Computational Intelligence

}  Swarm: data samples }  Habitat: grid of cells ◦  Each cell has a vector – randomly initialized - with same

cardinality as the data samples vectors.

}  Three rules: ◦  R1: move towards regions with more similar vectors. ◦  R2: update cell vector ◦  R3: evaporation - in each time-step, every vector of the

grid is again “pulled” towards its initial value.

2013 IEEE Symposium Series on Computational Intelligence

}  Result: ants/data samples tend to cluster.

2013 IEEE Symposium Series on Computational Intelligence

Example: Iris data set (quantifies the morphologic variation of Iris flowers of three related species)

Three classes: red: Setos, green: Versicolor, blue: Virginica

t=0 t=50 t=100 t=150

2013 IEEE Symposium Series on Computational Intelligence

Rule 2: update vectors

Rule 3: Evaporation

Rule 1: Move

Please note parameters β and δ. They define how the ants move.

Pi! j =w( j)r( j)w(k)r(k)

k"M#

2013 IEEE Symposium Series on Computational Intelligence

The swarm after 1000 iterations with different values for β and δ

There is a region of the parameter space in which the system self-organizes.

}  Remember Rule #2! ◦  Ants change the values of the habitat vectors.

}  Visualize the habitat grid. ◦  One variable – grey-level image ◦  Three variables – RGB or Lab. ◦  Four variables – 3-dimensional coloured image? ◦  More than four variables...

2013 IEEE Symposium Series on Computational Intelligence

data samples KANTS Grid

Translate to RGB

2013 IEEE Symposium Series on Computational Intelligence

Pherographia (drawing with pheromones) is based on an algorithm with same basic principles as KANTS. The algorithm detects the edges of grayscale images.

2013 IEEE Symposium Series on Computational Intelligence

Carlos M. Fernandes, The Horse and the Ants, 2008

C.M. Fernandes, Pherographia: Drawing by Ants, Leonardo 43(2), pp. 107-112, April 2010

}  Sleep data is used as input of the system. }  Hjorth parameters describe sleep

Electroencephalogram (EEG) with three-variable vectors.

}  Translation to RGB is trivial and direct. }  In a way, the images are representations of a

person’s sleep. }  Each person and each person’s night sleep

generates a different image: fingerprints of sleep.

2013 IEEE Symposium Series on Computational Intelligence

2013 IEEE Symposium Series on Computational Intelligence

2013 IEEE Symposium Series on Computational Intelligence

Data samples= list of RGB vectors

KANTS

Grid

Extract the data samples (three-variable RGB vectors) directly from a coloured image and then use these samples as KANTS output.

}  Winner of the Evolutionary, Design and Competition Art Competition (GECCO’12)

2013 IEEE Symposium Series on Computational Intelligence

Carlos M. Fernandes, Abstracting the Abstract #4 (after Kandinsky), 2012

2013 IEEE Symposium Series on Computational Intelligence

Carlos M. Fernandes, Abstracting the Abstract #5 (after Miró), 2012

2013 IEEE Symposium Series on Computational Intelligence

2013 IEEE Symposium Series on Computational Intelligence

2013 IEEE Symposium Series on Computational Intelligence

t=1 t=10 t=25 t=50

2013 IEEE Symposium Series on Computational Intelligence

photo β=8 β=16 β=32

2013 IEEE Symposium Series on Computational Intelligence

r = 10 r = 25 r = 50 r = 100

}  Devise other forms of representation when the cardinality of the vectors is >3

}  4-variables: maybe 3-dimensional representations.

}  Many variables. How to represent them?

2013 IEEE Symposium Series on Computational Intelligence

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