Animat Vision: Active Vision in Artificial Animals

Demetri Terzopoulos and Tamer F. Rabie
Department of Computer Science
University of Toronto


We propose and demonstrate a new paradigm for active vision research that draws upon recent advances in the fields of artificial life and computer graphics. A software alternative to the prevailing hardware vision mindset, animat vision prescribes artificial animals, or animats, situated in physics-based virtual worlds as autonomous virtual robots with active perception systems. To be operative in its world, an animat must autonomously control its eyes and muscle-actuated body. Computer vision algorithms continuously analyze the retinal image streams acquired by the animat's eyes, enabling it to locomote purposefully through its world. We describe an initial animat vision implementation within lifelike artificial fishes inhabiting a physics-based, virtual marine world. Emulating the appearance, motion, and behavior of real fishes in their natural habitats, these animats are capable of spatially nonuniform retinal imaging, foveation, retinal image stabilization, color object recognition, and perceptually-guided navigation. These capabilities allow them to pursue moving targets such as other artificial fishes.

Keywords: active vision, artificial life, artificial animals, autonomous agents, physics-based modeling, biomimetic vision systems, foveation, visual stabilization, color object detection, vision-guided navigation.