Semi-automatic 2D to 3D image conversion using scale-space Random Walks and a graph cuts based depth prior

In this paper, we present a semi-automated method for converting conventional 2D images into stereoscopic 3D. User-defined strokes corresponding to a rough estimate of the depth values in the scene are defined for the image of interest. With these, our system determines the depth values for the rest of the image, producing a depth map that can be used to create stereoscopic 3D image pairs. Our work is based on a similar scheme, using the Random Walks segmentation paradigm. However, the related work is quite complex, with many processing steps required to produce the final stereoscopic image pair. Combined with its evident shortcomings, but noting the merits, we propose a system employing Random Walks, while incorporating information from the popular Graph Cuts segmentation paradigm. Thus, a final cohesive depth map is produced, combining the merits of both. The results show that we can produce good quality stereoscopic image pairs, while using a much more simplified method in comparison to the related work.