George Mather
Research Interests

Movement perception

Animals move around to find mates, shelter, and food, and to avoid being eaten. Mobility brings with it the need to sense movement either of oneself or others, whether to aid safe navigation through the world, or to detect other mobile animals such as approaching predators. Most animals sense movement using their eyes. Special neurons in the visual system of the brain detect movement in the image cast into the eyes, and infer the character and cause of the movement. My research investigates how these neurons work, using experiments on human observers as well as computer simulations. Demonstrations of some of the moving images I and others have used to study human motion perception can be found on the Motion Demos section of the web site.

Psychology of visual art

Art-making is an endlessly fascinating area of human behavior. It can be studied from the perspective of many different disciplines, focusing onits cultural context, social history, technical development, and so on. The perspective I use as a vision scientist is based on experimental psychology and neuroscience. Visual art is a product of the brain. It depends in particular on the immense mass of neurons the make up the visual system of the brain, the parts which respond to light entering the eye. Activity in these neurons mediates all of our conscious visual experiences, including those we have when viewing art.
The visual system is arguably the most studied neural system in the brain. We know a huge amount about the properties of the visual system. It evolved to give us fast, accurate and precise information about the structure of the world around us; scene layout, objects, surface properties and so on. This scientific knowledge can be applied to help us understand some features of visual art. A few examples will help to illustrate the potential for dialogue between vision science and art.
Line drawing is the earliest form of expression in visual art. Ancient cave art contains many line-drawn depictions of animals such as lions, bulls and deer. None of the lines drawn in these works, and in other drawings, actually exist in the scene which the artist viewed. Images of real scenes do not contain areas of even illumination separated by thin, sharp lines. They contain only gradations of lightness and colour which vary in steepness. The brain constructs a codified internal representation of the scene, which delineates the shapes of surfaces and objects, and the textural markings on them. Drawing is a kind of ‘brain-dump’ of the representation, which viewers can understand implicitly because their brain uses the same coding scheme. Research in perception has been trying to deduce the code for years and is making some progress, but we are far from being able to predict (or simulate) this process in a computer vision system.
Similarly there are no colours in the real visual world, only large collections of light wavelengths emitted by or reflected from surfaces. ‘Colour’ is a purely subjective experience which is related to light wavelength, though not on the simple one-to-one basis implied by diagrams of the visible spectrum. Two particular pairs of colours have special significance for the visual system, and are consequently used frequently by artists, but these pairings have no reality or significance as far as physics is concerned. The pairs are red-green and blue-yellow. Due to the way that the brain analyses light wavelengths, these colour pairs complement or reinforce each other, and one can induce the other in neutral tones. The pairings are ubiquitous in art (Monet, Van Gogh, and Vermeer spring to mind. In most of Vermeer’s paintings blue tones are complemented by yellows; think of the “Girl with a Pearl Earring”). Some artists studiously avoid the colour pairs to throw us off balance. Bridget Riley, for example, avoids the use of complementary colours in her work because “the colour energy would be locked up in the complementary contrast, as though in a straightjacket. It is released by instability, a free floating flux”.
Representational paintings are almost always flat, yet we perceive depth in them. The depth is conveyed by cues which the visual system normally picks up from real three-dimensional scenes (converging or intersecting lines, diminishing size and so on). Artists were the first to discover that they can simulate some of these cues on a flat surface, and need not worry about the contradictory information from other cues (stereo, for example) because they can be discounted by the visual system. For instance subtle lightness gradation, or chiaroscuro, is used in art to model shape, and toning down of contrast, or sfumato, can convey distance. Artists also discovered that static pictorial art can be highly effective at conveying a sense of visual movement. Vision scientists have investigated this apparent paradox and found that static depictions of movement actually do stimulate the parts of the visual brain that are normally activated by real, dynamic movement.
By definition abstract art appears to have no connection with the identifiable surfaces and objects of natural scenes. But careful statistical analysis can reveal a subtle correspondence between the pictorial properties of natural scenes and abstract artworks. A few natural scenes (deserts, snow fields) contain very little variation in texture, lightness and colour, while others (dense woods, massed animal herds) contain an overwhelming amount of detail. But the majority of scenes occupies a middle ground, with moderate levels of textural detail, lightness variation and so on. These visual qualities can be measured by statistics such as fractal dimension. When the same measures are taken from large samples of abstract artworks (by many different artists) the same predominance of mid-level detail and texture is found as in natural scenes. This statistical match may indicate that artists tend to reproduce the visual ‘signature’ of natural scenes in their abstract art. Indeed some artists acknowledge that their work attempts to abstract or distil some essential property of natural scenes without depicting identifiable objects. The statistical match reveals their skill and judgement in the art of distillation.
The scientific perspective on art is a source of fascination to me. At the same time art is a hugely significant source of pleasure when I am outside the lab or office. Clearly science is not the only perspective one can take. It is just one of many equally valid perspectives, and cannot diminish the relevance of other perspectives. It gives a new way of seeing, to borrow a phrase from art history. It is up to you which ways of seeing interest you as a viewer, or indeed an artist.

Some of my recently published studies include research on:

Judgements of human stature in pictures and statues.

Preferences for orientation in abstract art.

The photograph in art.


ESRC Research Grant (2013-2016)
The Influence Of The Human Form On Visual Judgements Of Movement

Wellcome Trust Research Grant (2008-2011)
Computational and psychophysical studies of polarity effects in human visual motion processing

EPSRC Network Grant (2004-2005)
Network: Art and Science of Motion Perception

Wellcome Trust Research Grant (2000-2003)
Integrating models of motion analysis in the human visual system.

EPSRC Research Grant (1997-2000)
The use of image blur as a depth cue in human vision.

EPSRC Research Grant (1993-1996)
Psychophysical studies of interactions between first-order and second-order motion stimuli.

MRC Project Grant (1991-1993)
Temporal properties of low-level motion processes in human vision.

SERC Research Grant (1990-1993)
Perceptual studies of high level motion processing in the human visual system.

SERC Research Grant (1988-1991)
Psychophysical studies of the aperture problem in motion processing.

MRC Project Grant (1985-1988)
Spatial and temporal primitives involved in early processing of visual motion.