Wald's Sequential Analysis for Time-constrained Vision Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03151197" target="_blank" >RIV/68407700:21230/08:03151197 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Wald's Sequential Analysis for Time-constrained Vision Problems
Original language description
In detection and matching problems in computer vision, both classification errors and time to decision characterize the quality of an algorithmic solution. It is shown how to formalize such problems in the framework of sequential decision-making and derive quasi-optimal time-constrained solutions for three vision problems. The methodology is applied to face and interest point detection and to the RANSAC robust estimator. Error rates of the face detector proposed algorithm are comparable to the state-of-the-art methods. In the interest point application, the output of the Hessian-Laplace detector [Mikolajczyk-IJCV04] is approximated by a sequential WaldBoost classifier which is about five times faster than the original with comparable repeatability. A sequential strategy based on Wald's SPRT for evaluation of model quality in RANSAC leads to significant speed-up in geometric matching problems.
Czech name
Wald's Sequential Analysis for Time-constrained Vision Problems
Czech description
In detection and matching problems in computer vision, both classification errors and time to decision characterize the quality of an algorithmic solution. It is shown how to formalize such problems in the framework of sequential decision-making and derive quasi-optimal time-constrained solutions for three vision problems. The methodology is applied to face and interest point detection and to the RANSAC robust estimator. Error rates of the face detector proposed algorithm are comparable to the state-of-the-art methods. In the interest point application, the output of the Hessian-Laplace detector [Mikolajczyk-IJCV04] is approximated by a sequential WaldBoost classifier which is about five times faster than the original with comparable repeatability. A sequential strategy based on Wald's SPRT for evaluation of model quality in RANSAC leads to significant speed-up in geometric matching problems.
Classification
Type
C - Chapter in a specialist book
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA201%2F06%2F1821" target="_blank" >GA201/06/1821: Algorithms of image recognition</a><br>
Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Unifying Perspectives in Computational and Robot Vision
ISBN
978-0-387-75521-2
Number of pages of the result
21
Pages from-to
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Number of pages of the book
212
Publisher name
Springer
Place of publication
New York
UT code for WoS chapter
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