A Multiobjective Approach to Homography Estimation
Joint Authors
Zaldivar, Daniel
Cuevas, Erik
Osuna-Enciso, Valentín
Oliva, Diego
Zúñiga, Virgilio
Pérez-Cisneros, Marco
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-28
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
In several machine vision problems, a relevant issue is the estimation of homographies between two different perspectives that hold an extensive set of abnormal data.
A method to find such estimation is the random sampling consensus (RANSAC); in this, the goal is to maximize the number of matching points given a permissible error (Pe), according to a candidate model.
However, those objectives are in conflict: a low Pe value increases the accuracy of the model but degrades its generalization ability that refers to the number of matching points that tolerate noisy data, whereas a high Pe value improves the noise tolerance of the model but adversely drives the process to false detections.
This work considers the estimation process as a multiobjective optimization problem that seeks to maximize the number of matching points whereas Pe is simultaneously minimized.
In order to solve the multiobjective formulation, two different evolutionary algorithms have been explored: the Nondominated Sorting Genetic Algorithm II (NSGA-II) and the Nondominated Sorting Differential Evolution (NSDE).
Results considering acknowledged quality measures among original and transformed images over a well-known image benchmark show superior performance of the proposal than Random Sample Consensus algorithm.
American Psychological Association (APA)
Osuna-Enciso, Valentín& Cuevas, Erik& Oliva, Diego& Zúñiga, Virgilio& Pérez-Cisneros, Marco& Zaldivar, Daniel. 2015. A Multiobjective Approach to Homography Estimation. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099662
Modern Language Association (MLA)
Osuna-Enciso, Valentín…[et al.]. A Multiobjective Approach to Homography Estimation. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1099662
American Medical Association (AMA)
Osuna-Enciso, Valentín& Cuevas, Erik& Oliva, Diego& Zúñiga, Virgilio& Pérez-Cisneros, Marco& Zaldivar, Daniel. A Multiobjective Approach to Homography Estimation. Computational Intelligence and Neuroscience. 2015. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099662
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099662