Hierarchy and adaptivity in segmenting visual scenes

Eitan Sharon, Meirav Galun, Dahlia Sharon, Ronen Basri and Achi Brandt
Additional contact information
Eitan Sharon: The Weizmann Institute of Science
Meirav Galun: The Weizmann Institute of Science
Dahlia Sharon: Massachusetts General Hospital
Ronen Basri: The Weizmann Institute of Science
Achi Brandt: The Weizmann Institute of Science

Nature, 2006, vol. 442, issue 7104, 810-813

Abstract: Seeing things Humans usually can effortlessly find coherent regions even in noisy visual images, a task that is crucial for object recognition. Computer algorithms have been less successful at doing this in natural viewing conditions, in part because early work on the problem used only local computations on the image. Now a new approach has been developed, based on an image segmentation strategy that analyses all salient regions of an image and builds them into a hierarchical structure. This method is faster and more accurate than previous approaches, but the resulting algorithm is relatively simple to use. It is demonstrated in action by using it to find items within a large database of objects that match a target item.

Date: 2006
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DOI: 10.1038/nature04977

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