User assisted disparity remapping for stereo images

• A user assisted stereo image segmentation/disparity remapping method is proposed using superpixel primitives as graph nodes in the MRF based energy minimization framework.
• The technique provides a tool for emphasizing/de-emphasizing an object in the scene by virtually changing the depth in the direction of the camera axis.
• The proposed technique could also be used as a post-processing step for retargeting stereoscopic footage on different display sizes and resolutions.
• Quantitative and qualitative experiments verify the proposed hypothesis.

This study concentrates on user assisted disparity remapping for stereo image footage, i.e. the disparity of an object of interest is altered while leaving the remaining scene unattended. This application is useful in the sense that it provides a method for emphasizing/de-emphasizing an object on the scene by adjusting its depth with respect to the camera. The proposed technique can also be used as a post-processing step for retargeting stereoscopic footage on different display sizes and resolutions. The proposed technique involves an MRF-based energy minimization step for interactive stereo image segmentation, for which user assistance on only one of the stereo pairs is required for determining the location of stereo object pair. A key contribution of the proposed study is elimination of dense disparity estimation step from the pipeline. This step is realized through a sparse feature matching technique between the stereo pairs. Moreover, by the help of the proposed technique, novel disparity adjusted views are synthesized using the produced stereo object segments and background information for the images. Qualitative and quantitative evaluation of the generated segments and the disparity adjusted images prove the functionality and superiority of the proposed technique.