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Panorama Video App
Panoramic Video from Unstructured Camera Array
1,2F. Perazzi2A. Sorkine-Hornung2H. Zimmer2P. Kaufmann2O. Wang3S. Watson 1,2M. Gross
1ETH Zurich 2Disney Research Zurich 3Walt Disney Imagineering
Figure 1: Two panoramas created with our system. Top: a cropped frame from a 160 megapixel panoramic videogenerated from five input videos. The overlay on the right shows the fullpanorama, with the respective individual field of views of the input camerashighlighted by colored frames. Bottom: a crop from a 20 megapixelpanorama created from a highly unstructured array consisting of 14 cameras.
Abstract
We describe an algorithm for generating panoramic video from unstructured camera arrays. Artifact-freepanorama stitching is impeded by parallax between input views. Common strategies such as multi-level blendingor minimum energy seams produce seamless results on quasi-static input. However, on video input theseapproaches introduce noticeable visual artifacts due to lack of global temporal and spatial coherence. In thispaper we extend the basic concept of local warping for parallax removal. Firstly, we introduce an error measurewith increased sensitivity to stitching artifacts in regions with pronounced structure. Using this measure, ourmethod efficiently finds an optimal ordering of pair-wise warps for robust stitching with minimal parallax artifacts.Weighted extrapolation of warps in non-overlap regions ensures temporal stability, while at the same timeavoiding visual discontinuities around transitions between views. Remaining global deformation introduced by thewarps is spread over the entire panorama domain using constrained relaxation, while staying as close as possibleto the original input views. In combination, these contributions form the first system for spatiotemporally stablepanoramic video stitching from unstructured camera array input.
Introduction
We present an algorithm based on three key observations.Firstly, for the analysis of parallax errors we found existing image comparison techniques to be not sufficiently robust or targeted towards the specificstitching artifacts we observed. Hence, we introduce a patch-based error metricdefined on image gradients, which we designed to be especially sensitive toparallax errors in highly structured image regions, and which ensures visualsimilarity of content between the input videos and the output panorama.Secondly, the ability to compensate parallax errors between views depends onthe spatial configuration of the individual field of views and the scenecontent, and the order that the parallax is compensated between images. Wetherefore propose a method that first analyzes these properties, and thencomputes an optimized ordering of pair-wise image warps, which results inimproved quality of the paral lax removal. Our procedure remains efficient evenfor large numbers of input cameras, where brute-force approaches for finding anoptimal warp order would be infeasible. Finally, local image warpingaccumulates globally, leading to significant spatial deformations of thepanorama. Since these deformations are dependent on the per-frame scenecontent, they change for every output frame and hence result in noticeabletemporal jitter. We resolve these global deformations and temporal instabilityby a weighted warp extrapolation from overlap to non-overlap image regions, anda final constrained relaxation step of each full panoramic output frame to areference projection. We demonstrate panoramic video results captured withdifferent types of cameras on arrays with up to 14 cameras, allowing thegeneration of panoramic video in the order of tens to over a hundred megapixels
During A Panorama Video
Citation - BibTeX
Panorama Video Downloader App
F. Perazzi, A. Sorkine-Hornung, H. Zimmer, P. Kaufmann, O. Wang, S. Watson, M. Gross, Panoramic Video from Unstructured Camera Arrays, Computer Graphics Forum (Proc. Eurographics 2015), Vol. 34, No. 2, May 2015, Zurich, Switzerland. [ Pdf 9.0MB ][ BibTeX ][ Data ]