The "Camouflage Machine": optimising patterns for camouflage and visibility

Sometimes it is very important not to be seen: a well camouflaged tiger may catch its prey rather than go hungry; a concealed wildlife photographer may get the shot; and whilst much of the infrastructure of the modern environment (mobile telephone masts, wind farms etc.) is necessary, it is far from aesthetically pleasing - reducing visibility may be the difference between getting planning permission or not. In other words, as well as the obvious military applications, a systematic means of minimising the visibility of any object by finding its optimal camouflage pattern for a particular environment could be used in many other ways.
Just as it is sometimes important to minimise visibility, it can also be equally important to maximise it. From signalling in animals to maximising the visibility of warning signs, emergency vehicles, motorbikes and cyclists, there are plenty of examples where making something highly salient is important.
How could colour patterns to maximise or minimise visibility be created? There is no universally optimal camouflage: what works well in one place (the spots of a leopard, lying in wait in dappled foliage) may be less effective elsewhere (the same animal in a desert). Important factors which determine visibility include an object's size and viewing distance, its pattern of movement, and its height above the ground; the nature and variability of the environment(s) it will be concealed in, the lighting etc.
We will construct the "camouflage machine": a process to determine optimum camouflage or signalling patterns for a specific environment. Using state-of-the-art computational modelling techniques, our methodology (implemented in a computer programme) will allow the comparison and assessment of different approaches to visual concealment and signalling.
The camouflage machine will first be validated using two of our datasets of images (big cats and snakes). We will then cross validate the results for human observers and our existing computational model of the human visual system. At this point, we will be able to use the camouflage machine to assess the visibility of man-made objects, from military materiel to street furniture. Finally, we will release a publicly available application which, given an environment (characterised by photographs from this environment, a template of the object to be concealed, and a characterisation of the illumination in this environment), attempts to characterise the visibility function (the function mapping pattern characteristics to visibility), and provide an estimate of the minima (or maxima) of this function - the colouration pattern that would minimise (or maximise) the object's visibility in that environment.
In short, the project will yield a means of identifying the best covering pattern for any object in any environment, whether the aim is conspicuity or concealment.

Impact Summary
As this project will evaluate an unstudied property of materials that are both widespread in nature and of growing use in a range of industries, there are a range of beneficiaries in both academia and industry. Due to the charismatic and appealing nature of both iridescence and many of the species that produce it, this research will also have strong possibilities for public engagement activities.
Main beneficiaries of the project:
1) Industrial third parties (military, Cyclists' Touring Club, emergency services)
2) Public policymakers (Highways agency)
3) General public
4) Researchers, PI and Co-Is.
1) Industrial Third Parties.
The ability to specify an optimal camouflage pattern for any given environment has obvious implications for the military. Not least, it will allow expensive and lengthy field trials to be dramatically reduced, as the range of possible solutions can be constrained in advance using the "Camouflage Machine". We have existing relationships with QinetiQ (see supporting letter), DSTL and Malvern Optical, and are establishing one with BAE Systems. Through our established interactions, and by establishing new ones, this project will not only assist the maintenance of the UK's pre-eminence in camouflage research, but will also assist with the translation of that research into insights for several world leading UK industries.
The flip side of concealment is conspicuity, and this is something that the Cyclists' Touring Club has an interest in: what is the best way to make cyclists highly visible in cluttered and noisy urban environments? This line of enquiry should also be of interested to the emergency services: can fire engines, ambulances etc. be made optimally visible?
2) Public Policy Makers. The flip side of the concealment is visibility. The "Camouflage Machine" can be used to increase the visibility of street signs and reduce that of other street furniture. This has both safety and aesthetic implications, assessment of which could be of benefit to public policy makers such as the Highways Agency.
3) General Public. This topic would provide an excellent vehicle to provide activities that would engage the public. Camouflage lends itself to engaging demonstrations, and the "Camouflage Machine" would allow the public to see how to develop a pattern that is either well hidden, or very salient, in real time.
4) Researchers, PI and Co-Is. The two researchers employed on this grant would gain extensive training experience in an interdisciplinary range of novel techniques and experimental methods that have both academic and industrial relevance. As they will be closely collaborating throughout the project, this will allow a behavioural scientist to gain skills in computational modelling techniques, and vice versa. This is something we have previously achieved, with one recent PhD student from a psychology background now working as a postdoc in biology, and another student with a biology background now working on a psychophysics and modelling postdoc.
The PI and Co-Is will also benefit through the development of the "Camouflage Machine", as we predict that it will be of interest to many potential collaborators in both academia and industry, leading to additional future partnerships.