Vision on the Run: Resolving Moving Natural Images with Arthropod Eyes

Cornell Univ - State: Awds Made Prior May 2010, Ithaca NY

Investigators

Abstract

This comparative project addresses how information from the natural world is encoded by an animal's visual system to enable it to respond appropriately to resources, such as prey or mates, or stress sources, such as predators. The specific objective is to develop a rigorous quantitative understanding of the consequences of variation in photoreceptor performance in the eyes of two arthropods, a beetle and a crab, that live in relatively similar flat habitats, but which vary in their behavior, eye movements and types of objects to which they respond. As these animals move about their environment, the visual image will be blurred because the photoreceptors are too slow or too coarsely spaced. However, the blur may not be uniform throughout the image - photoreceptors that view regions of the world into which the animal is traveling or which are more likely to contain objects of interest may have been selected to perform better, whereas more blur in other areas of the visual field may be tolerable. We will combine anatomical and physiological data about photoreceptors over the eye with laboratory behavioral experiments and field recordings of natural scenes to learn how visual performance limits or enhances specific types of movement in the animal's natural world. The proposed research is the most comprehensive attempt to date to explore the transfer of information from natural scenes through an animal's photoreceptors during its normal behavior and will provide training in physiology, behavior, and scene analysis for young scientists and several undergraduate students, including underrepresented minorities who have worked in the lab in the past. The results will allow, for other species, important insight into the degree to which behavior-driven degradation of visual information may adversely affect adaptive behaviors. In addition to their basic application for sensory ecology, the results of this project will have a strong bearing on machine vision and will be valuable to robotics engineers attempting to design visual sensors that allow optimal robot performance. A postdoctoral scholar and undergraduate students will be involved in the research, and an interactive web site about the research will be created.