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Transcript
제6주. 응용-2: Graphics
Artificial Life for Computer Graphics
D. Terzopoulos, Communications of the ACM, vol. 42, no. 8,
pp. 33~42, 1999
학습목표
Understanding biological and evolutionary models to give life
to self-animating graphical characters with bodies, brains,
behavior, perception, learning and cognition
개요
 CG분야의 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
ALife
Cognitive
Behavioral
Physical
Kinematic
Geometric
Evolutionary
 Applications
– Motion picture special effects industry
• Stanley and Stella, Batman Returns, Cliffhanger, Lion King, Hercules,
Spawn, Mulan, Bug’s Life, etc
– Interactive games
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