Painting with Interactive Control of Perceptual Entropy

Painting with Interactive Control of Perceptual Entropy MINGTIAN ZHAO and SONG-CHUN ZHU, University of California, Los Angeles and Lotus Hill Institute In this article, we study a framework for generating abstract art from photographs. The aesthetics of abstract art, as a special category of visual arts, is largely attributed to its greater perceptual ambiguity than photographs. According to psychological theories [Berlyne 1971], the ambiguity tends to invoke moderate mental e↵orts of the viewer for interpreting the underlying contents, and this process is usually accompanied with subtle aesthetic pleasures. We study this phenomenon through human experiments comparing subjects’ interpretations of abstract art and photographs, and quantitatively verify the increased perceptual ambiguities in terms of recognition accuracy and response time. Based on the studies, we measure the level of perceptual ambiguity using entropy as it measures uncertainty levels in information theory, and propose a painterly rendering method with interactive control of the ambiguity levels. Given an input photograph, we first segment it into regions corresponding to di↵erent objects and parts in an interactive manner, and organize them into a hierarchical parse tree representation. Then we execute a painterly rendering process with image obscuring operators to transfer the photograph into an abstract painting style with increased perceptual ambiguities of both the scene and individual objects. Finally, using kernel density estimation and message passing algorithms, we compute and control the ambiguity levels numerically to the desired levels, during which we may predict and control the viewer’s perceptual path among the image contents by assigning di↵erent ambiguity levels to di↵erent objects. We have evaluated the rendering results using a second series of human experiments, and verified that they achieve similar abstract e↵ects to original abstract paintings by artists.