Pose-based composition improvement for portrait photographs

This paper studies the composition of portrait paintings and develops an algorithm to improve the composition of portrait photographs. The study of portrait paintings shows that placement of the face and the figure in portrait paintings is pose-related. Based on this observation, this paper develops an algorithm to improve the composition of a portrait photograph by learning the placement of the face and the figure from an example portrait painting. The example portrait painting is selected based on the similarity of its figure pose to that of the input photograph. This similarity measure is modeled as a graph matching problem. Finally, space cropping is performed using an optimization function. Experimental results and a user study demonstrate that the proposed pose-based improvement is preferred more than rule-based methods.