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<p dir="ltr">Collisions between birds and aircraft are a source of avian mortality, cause substantial economic damage, and are a major safety hazard for the global aviation industry. The theoretical frameworks attempting to explain animal behavioral responses to approaching high-speed vehicles are scarce. Some potential theoretical frameworks to apply have been developed for responses to natural predators. While both share similar principles, such as detection always precedes escape and escape responses require time to both initiate an enact (Chapter 1), antipredator theory is severely limited in the ability to predict behavioral responses to high-speed vehicles primarily because of the little time animals have to enact a response after such detection occurs (Chapter 1). A potential solution to mitigate the negative effects of vehicle approach speed is the use of lighting onboard a vehicle to increase the distance a threat is detected providing the animal with more time to escape. We assessed the behavioral responses of Canada geese (<i>Branta canadensis</i>), a frequently struck species capable of causing substantial damage, to lights of high chromatic contrast specific to their visual physiology. We first evaluated behavioral responses of different wavelengths of high chromatic contrast and identified that blue wavelengths tended to elicit avoidance responses over repeated exposures (Chapter 2). Subsequently, we assessed how the presence of high chromatic contrast blue lights influenced both goose detection and escape responses to an approaching aircraft (i.e., a drone or UAS) (Chapter 3). We found that lights of high chromatic contrast indeed resulted in early detection, but that also translated to earlier escape (Chapter 3). Lastly, we developed a model to answer a large outstanding question relevant to the use of lights to mitigate animal vehicle collisions: the distance at which a bird detects a light source (Chapter 4). Generally, our results suggest that the distance the avian visual system detects a light source increases as photon intensity increases but the magnitude of the increase heavily depends on light wavelength, the prevailing visibility, and ambient light conditions. Our research results are particularly relevant for the airline industry as well as low-altitude aircraft technology coming in the coming years.</p><p><br></p>

No / We explore the relative utility of shape from shading and binocular disparity for depth perception. Ray-traced images either featured a smooth surface illuminated from above (shading-only) or were defined by small dots (disparity-only). Observers judged which of a pair of smoothly curved convex objects had most depth. The shading cue was around half as reliable as the rich disparity information for depth discrimination. Shading- and disparity-defined cues where combined by placing dots in the stimulus image, superimposed upon the shaded surface, resulting in veridical shading and binocular disparity. Independently varying the depth delivered by each channel allowed creation of conflicting disparity-defined and shading-defined depth. We manipulated the reliability of the disparity information by adding disparity noise. As noise levels in the disparity channel were increased, perceived depths and variances shifted toward those of the now more reliable shading cue. Several different models of cue combination were applied to the data. Perceived depths and variances were well predicted by a classic maximum likelihood estimator (MLE) model of cue integration, for all but one observer. We discuss the extent to which MLE is the most parsimonious model to account for observer performance.

In this paper, we investigate how controlled changes to image properties and orientation affect eye movements for repeated viewings of images of natural scenes. We make changes to images by manipulating low-level image content (such as luminance or chromaticity) and/or inverting the image. We measure the effects of these manipulations on human scanpaths (the spatial and chronological path of fixations), additionally comparing these effects to those predicted by a widely used saliency model (L. Itti & C. Koch, 2000). Firstly we find that repeated viewing of a natural image does not significantly modify the previously known repeatability (S. A. Brandt & L. W. Stark, 1997; D. Noton & L. Stark, 1971) of scanpaths. Secondly we find that manipulating image features does not necessarily change the repeatability of scanpaths, but the removal of luminance information has a measurable effect. We also find that image inversion appears to affect scene perception and recognition and may alter fixation selection (although we only find an effect on scanpaths with the additional removal of luminance information). Additionally we confirm that visual saliency as defined by L. Itti and C. Koch's (2000) model is a poor predictor of real observer scanpaths and does not predict the small effects of our image manipulations on scanpaths.