Dynamic programming and graph algorithms in computer vision

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial gua...

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Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 33(2011), 4 vom: 07. Apr., Seite 721-40
1. Verfasser:	Felzenszwalb, Pedro F (VerfasserIn)
Weitere Verfasser:	Zabih, Ramin
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2011
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. Review


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520			\|a Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition
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