The images are organized into a tree with agglomerative clustering, using a measure of overlap as the distance. The reconstruction then follows this tree from the leaves to the root. As a result, the problems is broken into smaller instances, which are then separately solved and combined. Compared to the standard sequential approach, this pipeline boost computational efficiency by one order of magnitude, it is independent from the initial pair of views, and copes better with drift problems