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We present a method for easily generating depth maps from monoscopic (i.e. "2D") video footage in order to convert them into stereoscopic, or "3D", footage. Our method uses user-defined strokes for a number of keyframes in the original footage and interpolates between the keyframes to provide a sparse labelling for each frame. We then apply the Random Walks algorithm to the footage to provide depth estimates based on the input provided by the user. These depth maps can then be used to generate novel views through depthbased image rendering.Index Terms-random walks, depth maps, 2D-to-3D, stereoscopy, video

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.

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