Evolving Line Drawings
Ellie Baker
Margo I. Seltzer
Harvard University
Division of Applied Sciences
May 19, 1994
Goals
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Explore the power and limitations of interactive evolution
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Produce an artist's assistant
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achieve subtle highlighting and textural effects
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use a compact representation that is easily modified and transformed
Outline
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Introduction
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Interactive Evolution
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The Drawing Evolver
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Conclusions
Genetic Algorithms
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Model the process of biological evolution.
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Use random perturbations of a genome to create a population of "creatures."
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Apply a fitness criteria to select surviving creatures
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Repeat process
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Successfully applied to:
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Traveling Salesman Problem
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Graph Coloring
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Newspaper layout
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Animation of physically modeled figures
Interactive Evolution
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Use a human to provide fitness criteria
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Applicable where criteria is difficult to express computationally
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Previous applications
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biomorphs (Dawkins)
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face generation (Caldwell & Johnston)
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3D sculptures (Todd & Latham)
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abstract color images (Sims)
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Key component:
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evaluation of visual data
Drawing Evolver
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Use interactive evolution to create drawings.
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User need not be able to draw, just select desirable images.
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Use mutation to affect small changes to an existing drawing.
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Use mating to create a drawing with components of two parent drawings.
Key Questions
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Can we use interactive evolution to create specific images?
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Does this technique produce images that would be difficult to produce with MacDraw-like tools?
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Is the tool engaging?
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What is needed to make it useful?
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What are the areas in which interactive evolution is particularly powerful? weak?
Representation
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Drawing is represented as a collection of strokes.
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A stroke is:
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a collection of points
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stroke type
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a symmetry property
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a connection type
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a perturbation factor
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a mutation rate
Getting Started
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Two modes: Random and User-Input
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Random: Initial Population
Getting Started (2)
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User-Input: Initial Image
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User-Input: Evolved Images
Mutating
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Specify constraints to keep images in "face space".
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Randomly perturb points.
Mating
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Uniform Mating
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Independently select each stroke in each parent.
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Optionally weight stokes for inclusion.
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Face Application uses weightings of 0.3 - 0.7
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ID-Based Mating
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Group strokes into units (e.g. eyes, nose, mouth).
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Select entire group from one parent.
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Hybrid Mating
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For each set of strokes, select either Uniform or ID.
Uniform Mating
ID-Based Mating
Hybrid Mating
Resulting Images
Conclusions
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Achieves effects that are difficult with MacDraw-style drawing tools.
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Goal-oriented evolution is very difficult.
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For most people, a collection of pre-evolved images made the tool more engaging.
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Engaging for exploration.