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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Vydáno v:	IEEE transactions on pattern analysis and machine intelligence Ročník 33; číslo 4; s. 721 - 740
Hlavní autoři:	Felzenszwalb, P F, Zabih, R
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Los Alamitos, CA IEEE 01.04.2011 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithmics. Computability. Computer arithmetics Algorithms Application software Applied sciences Artificial intelligence Combinatorial algorithms Computer science Computer science; control theory; systems Computer Simulation Computer vision computing methodologies Dynamic programming Exact sciences and technology Graphs Image Enhancement - methods Image Processing, Computer-Assisted - methods Information retrieval. Graph Intelligence Interactive Layout Object segmentation Optimization Optimization methods Pattern analysis Pattern recognition. Digital image processing. Computational geometry Probability Stereo vision Theoretical computing Vision vision and scene understanding Vision, Ocular - physiology Computer vision Stereo image processing Image interpretation Combinatorial problem computing methodologies Modeling Optimization Image segmentation Combinatorial algorithms Scene analysis vision and scene understanding Problem solving Discrete programming Stereopsis Artificial intelligence
ISSN:	0162-8828, 1939-3539, 1939-3539
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Abstract	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.
AbstractList	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. 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.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. 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 non-trivial guarantees concerning solution quality. In this paper we briefly 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.
Author	Zabih, R Felzenszwalb, P F
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Snippet	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....
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SubjectTerms	Algorithmics. Computability. Computer arithmetics Algorithms Application software Applied sciences Artificial intelligence Combinatorial algorithms Computer science Computer science; control theory; systems Computer Simulation Computer vision computing methodologies Dynamic programming Exact sciences and technology Graphs Image Enhancement - methods Image Processing, Computer-Assisted - methods Information retrieval. Graph Intelligence Interactive Layout Object segmentation Optimization Optimization methods Pattern analysis Pattern recognition. Digital image processing. Computational geometry Probability Stereo vision Theoretical computing Vision vision and scene understanding Vision, Ocular - physiology
Title	Dynamic Programming and Graph Algorithms in Computer Vision
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