Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/77053
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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Szpak, Z. | - |
dc.contributor.author | Chojnacki, W. | - |
dc.contributor.author | Van Den Hengel, A. | - |
dc.contributor.editor | Fitzgibbon, A. | - |
dc.contributor.editor | Lazebnik, S. | - |
dc.contributor.editor | Perona, P. | - |
dc.contributor.editor | Sato, Y. | - |
dc.contributor.editor | Schmid, C. | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Proceedings of the 12th European Conference on Computer Vision, held in Florence, Italy, 7-13 October, 2012 / A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato and C. Schmid (eds.): pp.87-100 | - |
dc.identifier.isbn | 9783642337642 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.issn | 1611-3349 | - |
dc.identifier.uri | http://hdl.handle.net/2440/77053 | - |
dc.description.abstract | When faced with an ellipse fitting problem, practitioners frequently resort to algebraic ellipse fitting methods due to their simplicity and efficiency. Currently, practitioners must choose between algebraic methods that guarantee an ellipse fit but exhibit high bias, and geometric methods that are less biased but may no longer guarantee an ellipse solution. We address this limitation by proposing a method that strikes a balance between these two objectives. Specifically, we propose a fast stable algorithm for fitting a guaranteed ellipse to data using the Sampson distance as a data-parameter discrepancy measure. We validate the stability, accuracy, and efficiency of our method on both real and synthetic data. Experimental results show that our algorithm is a fast and accurate approximation of the computationally more expensive orthogonal-distance-based ellipse fitting method. In view of these qualities, our method may be of interest to practitioners who require accurate and guaranteed ellipse estimates. | - |
dc.description.statementofresponsibility | Zygmunt L. Szpak, Wojciech Chojnacki and Anton van den Hengel | - |
dc.language.iso | en | - |
dc.publisher | Springer-Verlag | - |
dc.relation.ispartofseries | Lecture Notes in Computer Science; 7576 | - |
dc.rights | © Springer-Verlag Berlin Heidelberg 2012 | - |
dc.source.uri | http://dx.doi.org/10.1007/978-3-642-33715-4_7 | - |
dc.title | Guaranteed ellipse fitting with the Sampson distance | - |
dc.type | Conference paper | - |
dc.contributor.conference | European Conference on Computer Vision (12th : 2012 : Florence, Italy) | - |
dc.identifier.doi | 10.1007/978-3-642-33715-4_7 | - |
dc.publisher.place | Germany | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Szpak, Z. [0000-0002-0694-4622] | - |
dc.identifier.orcid | Chojnacki, W. [0000-0001-7782-1956] | - |
dc.identifier.orcid | Van Den Hengel, A. [0000-0003-3027-8364] | - |
Appears in Collections: | Aurora harvest Computer Science publications |
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RA_hdl_77053.pdf Restricted Access | Restricted Access | 604.55 kB | Adobe PDF | View/Open |
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