PicWords: Render a Picture by Packing Keywords

Abstract

In this paper, we propose a novel text-art system: input a source picture and some keywords introducing the information about the picture, and the output is the so-called PicWords in the form of the source picture composed of the introduction keywords. Different from traditional text-graphics which are created by highly skilled artists and involve a huge amount of tedious manual work, PicWords is an automatic non-photorealistic rendering (NPR) packing system. Given a source picture, we first generate its silhouette, which is a binary image containing a Yang part and a Yin part. Yang part is for keywords placing while the Yin part can be ignored. Next, the Yang part is further over-segmented into small patches, each of which serves as a container for one keyword. To make sure that more important keywords are put into more salient and larger image patches, we rank both the patches and keywords and construct a correspondence between the patch list and keyword list. Then, mean value coordinates method is used for the keyword-patch warping. Finally, certain post-processing techniques are adopted to improve the aesthetics of PicWords. Extensive experimental results well demonstrate the effectiveness of the proposed PicWords system.