Multi-layered image retargeting

Shiori Sugimoto, Shinya Shimizu, Hideaki Kimata, Akira Kojima

Abstract: Pixel domain methods for content-aware image retargeting have a performance limitation in that they distort important objects when an image is shrunken too much. To address this problem, we have designed and developed a novel 3D space domain image retargeting which rearranges objects with occlusions and deforms objects. With this method image formation is modeled as a quasi-3D space. The method also reduces image width by shrinking a part of the image space. Instead of directly optimizing the position and shape of objects, it closes objects by shrinking the gap space between them and deforms objects by shrinking spaces that include parts of them. It is capable of being extended to higher dimension problems such as multi-view image retargeting because it needs to optimize only one quasi-3D space whether the input is ordinary images or more complex ones such as video and stereo images. We have also designed a simple algorithm that makes use of dynamic programming. An experiment we conducted demonstrated the algorithm's effectiveness.