Concealing 3D objects

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Camouflage is not just an adaptation to the physical environment, but to the perception and mind of the viewer. Billions of photons enter the eye every second, so vision reduces the information to only that which is normally useful. Because shortcuts are taken, sensory systems can be manipulated, and this is what camouflage does. Perceived differences in colour and texture are minimised, distinctive features are concealed, false edges are created and the cues the brain uses to group features into recognisable objects are disrupted. Therefore the study of animal camouflage gives us insights to how other species see the world, as well as an explanation for much of the diversity of animal colour and form that we see around us.Studying animal camouflage therefore has to be fundamentally interdisciplinary, bringing together concepts and tools from evolutionary and developmental biology, perceptual psychology and computer vision. This multi-pronged attack has, in the last decade, transformed our understanding, showing experimentally that specific mechanisms of concealment and disguise, many first postulated in the late 19th century, can work against animals with different visual systems from our own. But this evidence comes from either observational studies or experiments with artificial prey that (appropriately, given the aims) isolate specific mechanisms. What we can't do is point to a real animal and explain its colour pattern.Consider these issues. Cat species with spotty coats tend to live in forests and/or rest in trees; this suggests that spots are good camouflage in dappled lighting. Humans, at least, do indeed find them hard to detect. Are the different spot patterns of leopard, ocelot and jaguar equally good solutions for such habitats, differing only because of chance effects during their separate evolutionary histories? Or do the different spot patterns represent solutions to subtle differences in the habitats they occupy? Furthermore, are these patterns the optimal camouflage for animals of these sizes in these habitats, or are there other constraints or trade-offs at play? The reason we have not answered such questions (very general ones in evolutionary biology, about what constitutes evolutionary design or historical constraint) are threefold. First, we have not, until recently, had adequate ways of describing the patterns on animals, or backgrounds, as they would be represented in the brains of other species. Second, such modelling as has been attempted has only been applied to two-dimensional patterns (i.e. 'flat' animals or flat samples of a pattern). Third, we do not have equivalent data for the backgrounds against which animals might be seen (and at all relevant viewing angles). This grant proposal rectifies these shortfalls by applying novel computational methods ('deep learning' of the sort used by Google and their like) across three sub-projects, with different challenges and with different applications. All tackle long-standing, but unanswered, questions about the adaptive value of colour. Furthermore, the results will have direct application in the human domain.We have chosen three specific experimental systems - snails, cats and humans - because all have a solid background of research on which to build, but the colours operate at different spatial scales, against different viewers and, importantly, with different mechanisms for generating the patterns. All present new opportunities for a new, integrated approach to studying coloration and the interaction between pattern development and evolutionary function.Our research will also deliver a computational toolkit, and method, that can determine the best (or worst) camouflage for any object in any environment for any viewer (different species or, indeed, machine vision). This should prove useful not only for concealment, but the study of conspicuousness, in biology, advertising, warning signage, protective clothing and other applications.