Depth-based reference portrait painting selection for example-based rendering

The task objective concerned in this paper is to preserve the natural attributes of a photograph and only enhance its aesthetic perceptual feeling. The paper proposed to select reference portrait paintings based on depth for example-based photograph rendering to improve its aesthetic appeal. Hence, the rendered photograph acquires the aesthetic style as informed by the selected reference paintings. The depth attributes are based on the notions of foreground/background or figure/non-figure relationship. The analysis on portrait paintings suggests that the natural attributes can be measured by the lightness/saturation/hue distributions or contrasts within and between foreground and background. By segmenting the photograph and paintings based on the depth information, and computing the intra layer distributions and inter layer contrasts as the features for the similarity measurement, references are then selected from the top ranked paintings. Some rendering examples are presented in this paper for evaluating the performance of the selection method.