Title :
Structure-and-motion pipeline on a hierarchical cluster tree
Author :
Farenzena, Michela ; Fusiello, Andrea ; Gherardi, Riccardo
Author_Institution :
Dipt. di Inf., Univ. di Verona, Verona, Italy
fDate :
Sept. 27 2009-Oct. 4 2009
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.
Keywords :
computational complexity; image motion analysis; pattern clustering; agglomerative clustering; hierarchical cluster tree; low computational complexity; motion pipeline; structure pipeline; Computational complexity; Computer vision; Conferences; Global Positioning System; Image reconstruction; Pipelines; Surges; Tensile stress; Urban planning; Video sequences;
Conference_Titel :
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-4442-7
Electronic_ISBN :
978-1-4244-4441-0
DOI :
10.1109/ICCVW.2009.5457435