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Motivation

Animals in motion have intrigued computer graphics animators and researchers for several decades. They have long been the subject of study of zoologists and ethologists, and have recently helped inspire the emerging research discipline of artificial life.

In computer graphics, most animations of animals have been created using the traditional and often highly labour intensive keyframing technique, in which computers are employed to interpolate between animator-specified keyframes [Lasseter1987]. More recently, increasingly automated techniques for synthesizing realistic animal motion have drawn much attention. Successful attempts have been made to animate the motions of humans [Magnenat-Thalmann and Thalmann1990, Hodgins, Sweeney and Lawrence1992], of certain animals [Miller1988, Girard1991] and of some imaginary creatures [Witkin and Kass1988, van de Panne and Fiume1993, Ngo and Marks1993]. However, motion synthesis is only part of the challenge of animating animals. Some group behaviors evident in the animal world, such as flocking, schooling and herding [Reynolds1987] have also been simulated and realistically animated in recent feature films.

In this dissertation, we will investigate the problem of producing animation which captures the intricacy of motion and behavior evident in certain natural ecosystems. These animations are intrinsically complex and present a challenge to the computer graphics practitioner. Animations of this sort are of interest not only because they attempt to recreate fascinating natural scenarios, but also because they have broad applicability. They can be used in the entertainment industry, for special effects in movies, for video games, for virtual reality rides; as well as in education as, say, interactive educational tools for teaching biology.

Our goal will be to create the animations that we have described, not by conventional keyframing, but rather through the sophisticated modeling of animals and their habitats. To this end, we have been motivated by and have contributed to the artificial life (ALife) movement [Levy1992]. ALife complements the traditional analytic approach of biology by aiming to understand natural life through synthetic, computational means. That is to say, rather than studying biological phenomena by analyzing living systems, the ALife approach attempts to synthesize artificial systems that behave like living organisms. An important area of ALife research is the synthesis of artificial animals--or ``animats''--implemented both in software and in hardware [Meyer and Guillot1991, Cliff et al.1994]. Computational models of simple animals, such as single-cell life forms [Langton1987] and insects [Beer1990], have been proposed with interesting results. Many of these models draw upon theories of animal behavior put forward by ethologists [Manning1979, McFarland1971].

Since we will view the animation of natural ecosystems as the process of visualizing computer simulations of animals in their habitats, our work straddles the boundary between the fields of computer graphics and artificial life. This theme has also been investigated by Terzopoulos et al. dt-s95-course.


next up previous contents
Next: Challenges Up: Introduction Previous: Introduction
Xiaoyuan TuJanuary 1996