Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107905
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Type: Conference paper
Title: A study of the region covariance descriptor: impact of feature selection and image transformations
Author: Faulkner, H.
Shehu, E.
Szpak, Z.
Chojnacki, W.
Tapamo, J.
Dick, A.
Van Den Hengel, A.
Citation: Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2015 / pp.1-8
Publisher: IEEE
Issue Date: 2015
ISBN: 9781467367950
Conference Name: International Conference on Digital Image Computing: Techniques and Applications (DICTA) (23 Nov 2015 - 25 Nov 2015 : Adelaide, SA.)
Statement of
Responsibility: 
Hayden Faulkner, Ergnoor Shehu, Zygmunt L. Szpak, Wojciech Chojnacki Jules R. Tapamo, Anthony Dick and Anton van den Hengel
Abstract: We analyse experimentally the region covariance descriptor which has proven useful in numerous computer vision applications. The properties of the descriptor—despite its widespread deployment—are not well understood or documented. In an attempt to uncover key attributes of the descriptor, we characterise the interdependence between the choice of features and distance measures through a series of meticulously designed and performed experiments. Our results paint a rather complex picture and underscore the necessity for more extensive empirical and theoretical work. In light of our findings, there is reason to believe that the region covariance descriptor will prove useful for methods that perform image super-resolution, deblurring, and denoising based on matching and retrieval of image patches from an image dictionary.
Rights: © 2015 IEEE
RMID: 0030045638
DOI: 10.1109/DICTA.2015.7371222
Published version: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7371187
Appears in Collections:Computer Science publications

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