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.

• Type: Conference
• Year: 2003
• Where: ICCV
• Authors: Christoph Strecha, Tinne Tuytelaars, Luc J. Van Gool
• Keywords: Computer Vision, Dense Depth Extraction, Fine Grained Fashion, ICCV 2003, Multiple Wide-baseline Images, Multiple Wide-baseline Views, Reliable Information Spreads