Efficient Multi-image Correspondences for On-line Light Field Video Processing

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dc.contributor.authorDąbała, Łukaszen_US
dc.contributor.authorZiegler, Matthiasen_US
dc.contributor.authorDidyk, Piotren_US
dc.contributor.authorZilly, Frederiken_US
dc.contributor.authorKeinert, Joachimen_US
dc.contributor.authorMyszkowski, Karolen_US
dc.contributor.authorSeidel, Hans-Peteren_US
dc.contributor.authorRokita, Przemysławen_US
dc.contributor.authorRitschel, Tobiasen_US
dc.contributor.editorEitan Grinspun and Bernd Bickel and Yoshinori Dobashien_US
dc.date.accessioned2016-10-11T05:20:47Z
dc.date.available2016-10-11T05:20:47Z
dc.date.issued2016
dc.description.abstractLight field videos express the entire visual information of an animated scene, but their shear size typically makes capture, processing and display an off-line process, i. e., time between initial capture and final display is far from real-time. In this paper we propose a solution for one of the key bottlenecks in such a processing pipeline, which is a reliable depth reconstruction possibly for many views. This is enabled by a novel correspondence algorithm converting the video streams from a sparse array of off-the-shelf cameras into an array of animated depth maps. The algorithm is based on a generalization of the classic multi-resolution Lucas-Kanade correspondence algorithm from a pair of images to an entire array. Special inter-image confidence consolidation allows recovery from unreliable matching in some locations and some views. It can be implemented efficiently in massively parallel hardware, allowing for interactive computations. The resulting depth quality as well as the computation performance compares favorably to other state-of-the art light field-to-depth approaches, as well as stereo matching techniques. Another outcome of this work is a data set of light field videos that are captured with multiple variants of sparse camera arrays.en_US
dc.description.number7
dc.description.sectionheadersImages and Video
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume35
dc.identifier.doi10.1111/cgf.13037
dc.identifier.issn1467-8659
dc.identifier.pages401-410
dc.identifier.urihttps://doi.org/10.1111/cgf.13037
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13037
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.4.8 [Image processing and Computer Vision]
dc.subjectScene Analysis
dc.subjectShape
dc.titleEfficient Multi-image Correspondences for On-line Light Field Video Processingen_US
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