제 6 주 . 응용 -2: GraphicsArtificial Life for Computer Graphics

D. Terzopoulos, Communications of the ACM, vol. 42, no. 8, pp. 33~42, 1999

학습목표Understanding biological and evolutionary models to give life to self-animating graphical characters with bodies, brains, beh

avior, perception, learning and cognition

개요 CG 분야의 발전방향

– Purely geometric models more elaborate physics-based models

– A world of objects of much greater complexity that looks alive

Artificial life

– Construction of advanced graphics models for image synthesis, animation, multimedia, and virtual reality

– Incorporation of state-of-the-art geometric and physics-based modeling techniques

– Natural process to simulation

• Birth and death, growth and development, natural selection, evolution, perception, locomotion, manipulation, adaptive behavior, learning, intelligence

– Goal: elf-creating, self-evolving, self-controling, self-animating

Signs of ALife

Modeling hierarchy

Applications

– Motion picture special effects industry

• Stanley and Stella, Batman Returns, Cliffhanger, Lion King, Hercules, Spawn, Mulan, Bug’s Life, etc

– Interactive games

CognitiveBehavioral

PhysicalKinematicGeometric

ALife Evolutionary

Applications Artificial plants

– L-systems (formal language framework) to grow highly complex and realistic graphics models of plants

Artificial evolution

– Karl Sims’ evolutionary work for graphics (survival of the fittest) Behavioral modeling and animation

– Craig Reynolds’ boids experiment: form of behavioral rules governing interaction of multiple autonomous agents capable of locomotion and perception within a virtual world

Artificial animals

– Motor control, perception, behavior, learning, cognition Artificial humans

– Sensory perception in human modeling, equipping virtual humans with visual, tactile, and auditory sensors sensory awareness

Interactive synthetic characters

– Creatures, ALIVE, Swamped

Lifelike Autonomous Agents

Artificial Fishes

– X. Tu at Univ. of Toronto

– Autonomous agent with a deformable body actuated by internal muscles

– Eye, brain, motor, perception, behavior, learning centers

– Perceptual awareness of the virtual world

– Collision avoidance, foraging, preying, schooling, mating

– Digitized photographs through computer vision techniques

– Lagrangian equations of motion (69 equations per fish)

– Primitive, reflexive behavior routines: obstacle avoidance

– More sophisticated motivational behavior routines: schooling, mating

– Cognitive capacity with action-selection mechanism

– SMART Toronto (www.sto.org)

– Trimension Reality Theater (www.trimension-inc.com)

Conclusion

Alife’s role in computer graphics

– Image synthesis, modeling, animation, interactive games, multimedia, virtual reality

Challenge to graphics researchers

– Develop and creatively deploy ever more sophisticated graphics models by simulating the mechanisms of life