For example, by analysing brush strokes, colour and style, AI-driven tools are revealing how artists' understanding of the science of optics has helped them to convey light and perspective. Programs are recovering the appearance of lost or hidden artworks and even computing the 'meanings' of some paintings, by identifying symbols, for example.
Most art historians still rely on their individual expertise when judging artists' techniques by eye, backed up with laboratory, library and leg work to pin down dates, materials and provenance. Computer scientists, meanwhile, find it easier to analyse 2D photographs or digital images than layers of oil pigments styled with a brush or palette knife. Yet, collaborations are springing up between computer scientists and art scholars.
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