2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops
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Abstract

This papers introduces a novel hierarchical scheme for computing Structure and Motion. The images are organized into a tree with agglomerative clustering, using a measure of overlap as the distance. The reconstruction follows this tree from the leaves to the root. As a result, the problem is broken into smaller instances, which are then separately solved and combined. Compared to the standard sequential approach, this framework has a lower computational complexity, it is independent from the initial pair of views, and copes better with drift problems. A formal complexity analysis and some experimental results support these claims.
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