View interpolation for image synthesis
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Plenoptic modeling: an image-based rendering system
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
The digital Michelangelo project: 3D scanning of large statues
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Unstructured lumigraph rendering
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Proceedings of the conference on Visualization '02
Polymorph: Morphing Among Multiple Images
IEEE Computer Graphics and Applications
3-D Scene Data Recovery using Omnidirectional Multibaseline Stereo
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Sea of Images: A Dense Sampling Approach for Rendering Large Indoor Environments
IEEE Computer Graphics and Applications
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Presence: Teleoperators and Virtual Environments
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
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Image-based rendering (IBR) systems enable virtual walkthroughs of photorealistic environments by warping and combining reference images to novel viewpoints under interactive user control. A significant challenge in such systems is to automatically compute image correspondences that enable accurate image warping.In this paper, we describe a new algorithm for computing a globally consistent set of image feature correspondences across a wide range of viewpoints suitable for IBR walkthroughs. We first detect point features in a dense set of omnidirectional images captured on an eye-height plane. Then, we track these features from image to image, identifying potential correspondences when two features track to the same position in the same image. Among the potential correspondences, we select the maximal consistent set using a greedy graph-labeling algorithm.A key feature of our approach is that it exploits the multiple paths that can be followed between images in order to increase the number of feature correspondences between distant images. We demonstrate the benefits of this approach in a real-time IBR walkthrough system where novel images are reconstructed as the user moves interactively.