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Seamless Image Stitching of Scenes with Large Motions and Exposure Differences

Ashley Eden, Matthew Uyttendaele, and Richard Szeliski

Abstract

This paper presents a technique to automatically stitch multiple images at varying orientations and exposures to create a composite panorama that preserves the angular extent and dynamic range of the inputs. The main contribution of our method is that it allows for large exposure differences, large scene motion or other misregistrations between frames and requires no extra camera hardware. To do this, we introduce a two-step graph cut approach. The purpose of the first step is to fix the positions of moving objects in the scene. In the second step, we fill in the entire available dynamic range. We introduce data costs that encourage consistency and higher signal-to-noise ratios, and seam costs that encourage smooth transitions. Our method is simple to implement and effective. We demonstrate the effectiveness of our approach on several input sets with varying exposures and camera orientations.

Details

Publication typeInproceedings
Published inIEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2006)
Pages2498-2505
Volume3
AddressNew York, NY
PublisherIEEE Computer Society
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