Dense Matching of Multiple Wide-baseline Views

This paper describes a PDE-based method for dense depth extraction from multiple wide-baseline images. Emphasis lies on the usage of only a small amount of images. The integration of these multiple wide-baseline views is guided by the relative confidence that the system has in the matching to different views. This weighting is fine-grained in that it is determined for every pixel at every iteration. Reliable information spreads fast at the expense of less reliable data, both in terms of spatial communications within a view and in terms of information exchange between the views. Changes in intensity between images can be handled in a similar fine grained fashion.

Published in:
2, 1194-1201
Presented at:
9th IEEE International Conference on Computer Vision, Nice, October 13-16, 2003

 Record created 2008-10-07, last modified 2018-01-28

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