Megastereo: Constructing High-Resolution Stereo Panoramas

Christian Richardt, Yael Pritch, Henning Zimmer, Alexander Sorkine-Hornung

Research output: Chapter or section in a book/report/conference proceedingChapter or section

83 Citations (SciVal)


We present a solution for generating high-quality stereo panoramas at megapixel resolutions. While previous approaches introduced the basic principles, we show that those techniques do not generalise well to today’s high image resolutions and lead to disturbing visual artefacts. As our first contribution, we describe the necessary correction steps and a compact representation for the input images in order to achieve a highly accurate approximation to the required ray space. Our second contribution is a flow-based upsampling of the available input rays which effectively resolves known aliasing issues like stitching artefacts. The required rays are generated on the fly to perfectly match the desired output resolution, even for small numbers of input images. In addition, the upsampling is real-time and enables direct interactive control over the desired stereoscopic depth effect. In combination, our contributions allow the generation of stereoscopic panoramas at high output resolutions that are virtually free of artefacts such as seams, stereo discontinuities, vertical parallax and other mono-/stereoscopic shape distortions. Our process is robust, and other types of multi-perspective panoramas, such as linear panoramas, can also benefit from our contributions. We show various comparisons and high-resolution results.
Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
Subtitle of host publication23-28 June 2013, Portland, Oregon, USA
Place of PublicationLos Alamitos, CA, USA
Number of pages8
ISBN (Print)978-0-7695-4989-7
Publication statusPublished - 3 Oct 2013
EventIEEE International Conference on Computer Vision and Pattern Recognition (CVPR) - Oregon, US, UK United Kingdom
Duration: 25 Jun 201327 Jun 2013


ConferenceIEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
Country/TerritoryUK United Kingdom
CityOregon, US


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