Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/85354
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bab-Hadiashar, A. | - |
dc.contributor.author | Suter, D. | - |
dc.date.issued | 1999 | - |
dc.identifier.citation | Robotica, 1999; 17(6):649-660 | - |
dc.identifier.issn | 0263-5747 | - |
dc.identifier.issn | 1469-8668 | - |
dc.identifier.uri | http://hdl.handle.net/2440/85354 | - |
dc.description.abstract | A method of data segmentation, based upon robust least K-th order statistical model fitting (LKS), is proposed and applied to image motion and range data segmentation. The estimation method differs from other approaches using versions of LKS in a number of important ways. Firstly, the value of K is not determined by a complex optimization routine. Secondly, having chosen a fit, the estimation of scale of the noise is not based upon the K-th order statistic of the residuals. Other aspects of the full segmentation scheme include the use of segment contiguity to: (a) reduce the number of random sample fits used in the LKS stage, and (b) to “fill-in” holes caused by isolated miss-classified data. | - |
dc.description.statementofresponsibility | Alireza Bab-Hadiashar and David Suter | - |
dc.language.iso | en | - |
dc.publisher | Cambridge University Press | - |
dc.rights | © 1999 Cambridge University Press | - |
dc.source.uri | http://dx.doi.org/10.1017/s0263574799001812 | - |
dc.subject | Robust segmentation; Visual data; Scale estimate; LKS method; Robust statistic | - |
dc.title | Robust segmentation of visual data using ranked unbiased scale estimate | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1017/S0263574799001812 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Suter, D. [0000-0001-6306-3023] | - |
Appears in Collections: | Aurora harvest 2 Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.