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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