| Augusto Román Stanford University | Hendrik P. A. Lensch Stanford University | |
| To appear in the Proceedings of EGSR 2006 | ||
Paper
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Abstract
Multiperspective images generated from a collection of photographs or a videostream can be used to effectively summarize long, roughly planar scenes such as city streets. The final image can span a larger field of view than any single input image. However, common projections used to make these images, including the cross-slits and pushbroom projections, may suffer from depth-related distortions in non-planar scenes. In this paper, we propose a metric for evaluating the distortion in these images due to deviation from the standard perspective projection. Minimizing this error metric we can automatically define the picture surface and viewpoints of a multiperspective image to reduce the distortion artifacts. This optimization requires only a coarse estimate of scene geometry, which can be provided as a depth map or in the form of a 2D spatial importance map defining interesting parts of the scene. These maps can be automatically constructed in many cases, allowing rapid generation of images of very long scenes.
Long result