Concealing 3D objects

伪装不仅仅是对自然环境的一种适应，也是对观者的感知和思维的一种适应。每秒有数十亿光子进入眼睛，因此视觉将信息减少到只有通常有用的信息。因为走捷径，感觉系统可以被操纵，这就是伪装的作用。颜色和纹理的感知差异被最小化，独特的特征被隐藏，虚假的边缘被创造出来，大脑用来将特征归类为可识别物体的线索被打乱。因此，对动物伪装的研究让我们了解了其他物种是如何看待世界的，也解释了我们周围动物颜色和形态的多样性。因此，研究动物伪装必须从根本上是跨学科的，汇集了进化和发育生物学、感知心理学和计算机视觉的概念和工具。在过去的十年里，这种多管齐下的攻击已经改变了我们的理解，实验表明，隐藏和伪装的特定机制（许多最初是在19世纪后期提出的）可以对付与我们自己的视觉系统不同的动物。但这些证据要么来自观察性研究，要么来自人工猎物的实验，这些实验（适当地，考虑到目标）分离出了特定的机制。我们不能做的是指着一只真正的动物并解释它的颜色图案。考虑这些问题。有斑点皮毛的猫倾向于生活在森林和/或在树上休息；这表明斑点在斑驳的光线下是很好的伪装。至少，人类确实发现它们很难被发现。豹子、豹猫和美洲虎身上不同的斑点图案是否同样适用于这样的栖息地，它们的不同仅仅是因为它们各自的进化史中的偶然影响？或者不同的斑点模式代表了它们所占据栖息地的细微差异的解决方案？此外，这些图案是这些栖息地中这些体型的动物的最佳伪装，还是有其他的限制或权衡？我们没有回答这些问题（在进化生物学中非常普遍的问题，关于什么构成了进化设计或历史约束）的原因有三个。首先，直到最近，我们还没有足够的方法来描述动物或背景上的图案，因为它们会在其他物种的大脑中表现出来。其次，已经尝试的这种建模只应用于二维模式(即。“扁平的”动物或图案的扁平样本)。第三，我们没有关于动物可能被看到的背景（以及所有相关视角）的等效数据。这项拨款提案通过在三个具有不同挑战和不同应用的子项目中应用新颖的计算方法（谷歌等使用的那种“深度学习”）来纠正这些不足。所有这些都解决了关于颜色的适应价值的长期存在但没有答案的问题。此外，研究结果将直接应用于人类领域。我们选择了三个特定的实验系统——蜗牛、猫和人类——因为它们都有坚实的研究背景，但是颜色在不同的空间尺度上运行，针对不同的观众，重要的是，产生图案的机制不同。所有这些都为研究颜色以及图案发育和进化功能之间的相互作用提供了新的、综合的方法。我们的研究还将提供一个计算工具包和方法，可以为任何环境中的任何物体（不同物种或机器视觉）确定最佳（或最差）伪装。事实证明，这不仅对隐藏有用，而且对生物学、广告、警告标志、防护服和其他应用中的显著性研究也很有用。

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.