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Synopsis
This work deals with the computer vision problem of recognizing and locating rigid shapes in the plane which have been subjected to unknown rotation, scaling, and noise. The recognition task includes both locating the overall pattern and identifying each of its features. Location is achieved by finding a geometric registration function that does a good job of superimposing the instance and the model. Identifying the features requires matching each model feature with the corresponding instance feature.
A pruned tree-search algorithm is developed which makes effective use of the Soviet ellipsoid algorithm for feasibility of linear constraints. An interesting blend of theoretical analysis and practical implementation shows that the resulting algorithm has an expected runtime that is theoretically asymptotically quadratic in the number of feature points, but practically linear in n for patterns with fewer than 100 points.
Contents: Introduction; Task Abstraction; Prior Approaches; A Linear Programming Approach; Geometry of Registrations and Ellipsoids; Worst-Case Number of Feasible Matchings; Random Patterns; Expected Cost of Feasibility Testing; Expected Size of Search Tree; Monte Carlo Trials; Conclusions.
Henry S. Baird received his doctorate from Princeton University. He is currently a technical staff member et AT & T Bell Laboratories. Model-Based Image Matching Using Location is a 1984 ACM Distinguished Dissertation.
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- PublisherMit Pr
- Publication date1985
- ISBN 10 0262022206
- ISBN 13 9780262022200
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages128
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Model-Based Image Matching Using Location (ACM Distinguished Dissertation)
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Model-based Image Matching Using Location (ACM distinguished dissertations)
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Hardcover. Condition: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 1985. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Edition 1985. Ammareal gives back up to 15% of this item's net price to charity organizations. Seller Inventory # E-863-199
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Model-based Image Matching Using Location (ACM distinguished dissertations)
Seller: Ammareal, Morangis, France
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Hardcover. Condition: Bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 1985. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slight signs of wear on the cover. Edition 1985. Ammareal gives back up to 15% of this item's net price to charity organizations. Seller Inventory # E-563-623
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Model-Based Image Matching Using Location (ACM Distinguished Dissertation).
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Condition: as new. Cambridge, MA: The MIT Press, 1985. Hardcover. 128 pp.- This work deals with the computer vision problem of recognizing and locating rigid shapes in the plane which have been subjected to unknown rotation, scaling, and noise. The recognition task includes both locating the overall pattern and identifying each of its features. Location is achieved by finding a geometric registration function that does a good job of superimposing the instance and the model. Identifying the features requires matching each model feature with the corresponding instance feature. A pruned tree-search algorithm is developed which makes effective use of the Soviet ellipsoid algorithm for feasibility of linear constraints. An interesting blend of theoretical analysis and practical implementation shows that the resulting algorithm has an expected runtime that is theoretically asymptotically quadratic in the number of feature points, but practically linear in n for patterns with fewer than 100 points. English text. Condition : as new. Condition : as new copy. ISBN 9780262022200. Keywords : , Pattern recognition. Seller Inventory # 263330
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Model-Based Image Matching Using Location (ACM Distinguished Dissertation)
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