Split-Depth Image Generation and Optimization

dc.contributor.authorLiao, Jingtangen_US
dc.contributor.authorEisemann, Martinen_US
dc.contributor.authorEisemann, Elmaren_US
dc.contributor.editorJernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornungen_US
dc.date.accessioned2017-10-16T05:24:24Z
dc.date.available2017-10-16T05:24:24Z
dc.date.issued2016
dc.description.abstractSplit-depth images use an optical illusion, which can enhance the 3D impression of a 2D animation. In split-depth images (also often called split-depth GIFs due to the commonly used file format), static virtual occluders in form of vertical or horizontal bars are added to a video clip, which leads to occlusions that are interpreted by the observer as a depth cue. In this paper, we study different factors that contribute to the illusion and propose a solution to generate split-depth images for a given RGB + depth image sequence. The presented solution builds upon a motion summarization of the object of interest (OOI) through space and time. It allows us to formulate the bar positioning as an energy-minimization problem, which we solve efficiently. We take a variety of important features into account, such as the changes of the 3D effect due to changes in the motion topology, occlusion, the proximity of bars or the OOI, and scene saliency. We conducted a number of psycho-visual experiments to derive an appropriate energy formulation. Our method helps in finding optimal positions for the bars and, thus, improves the 3D perception of the original animation. We demonstrate the effectiveness of our approach on a variety of examples. Our study with novice users shows that our approach allows them to quickly create satisfying results even for complex animations.en_US
dc.description.number7
dc.description.sectionheadersReconstruction and Generation based on RGBD Images
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.13283
dc.identifier.issn1467-8659
dc.identifier.pages175-182
dc.identifier.urihttps://doi.org/10.1111/cgf.13283
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13283
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectImage processing
dc.subjectPerception
dc.titleSplit-Depth Image Generation and Optimizationen_US
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