Performance evaluation of single and cross-dimensional feature detection and description

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dc.contributor.authorKechagias-Stamatis, Odysseas
dc.contributor.authorAoufi, Abdelkader
dc.contributor.authorRichardson, Mark A.
dc.date.accessioned2020-03-02T15:13:37Z
dc.date.available2020-03-02T15:13:37Z
dc.date.issued2019-10-18
dc.description.abstractThree-dimensional local feature detection and description techniques are widely used for object registration and recognition applications. Although several evaluations of 3D local feature detection and description methods have already been published, these are constrained in a single dimensional scheme, i.e. either 3D or 2D methods that are applied onto multiple projections of the 3D data. However, cross-dimensional (mixed 2D and 3D) feature detection and description has yet to be investigated. Here, we evaluated the performance of both single and cross-dimensional feature detection and description methods on several 3D datasets and demonstrated the superiority of cross-dimensional over single-dimensional schemes.en_UK
dc.identifier.citationKechagias-Stamatis O, Aouf N, Richardson MA. (2020) Performance evaluation of single and cross-dimensional feature detection and description, IET Image Processing, Volume 14, Issue 10, August 2020, pp. 2035-2051en_UK
dc.identifier.urihttps://doi.org/ 10.1049/iet-ipr.2019.1523
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/15203
dc.language.isoenen_UK
dc.publisherInstitution of Engineering and Technology (IET)en_UK
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.titlePerformance evaluation of single and cross-dimensional feature detection and descriptionen_UK
dc.typeArticleen_UK

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