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Content-driven superpixels and their applications

Content-driven superpixels and their applications
Content-driven superpixels and their applications
This thesis develops a new superpixel algorithm that displays excellent visual reconstruction of the original image. It achieves high stability across multiple random initialisations, achieved by producing superpixels directly corresponding to local image complexity. This is achieved by growing superpixels and dividing them on image variation. The existing analysis was not sufficient to take these properties into account so new measures of oversegmentation provide new insight into the optimum superpixel representation. As a consequence of the algorithm, it was discovered that CDS has properties that have eluded previous attempts, such as initialisation invariance and stability. The completely unsupervised nature of CDS makes them highly suitable for tasks such as application to a database containing images of unknown complexity. These new superpixel properties have allowed new applications for superpixel pre-processing to be produced. These are image segmentation; image compression; scene classification; and focus detection. In addition, a new method of objectively analysing regions of focus has been developed using Light-Field photography.
Lowe, Richard
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Lowe, Richard
d597842e-560d-44a0-bade-dee08ce57677
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

(2013) Content-driven superpixels and their applications. University of Southampton, Faculty of Physical Science and Engineering, Doctoral Thesis, 113pp.

Record type: Thesis (Doctoral)

Abstract

This thesis develops a new superpixel algorithm that displays excellent visual reconstruction of the original image. It achieves high stability across multiple random initialisations, achieved by producing superpixels directly corresponding to local image complexity. This is achieved by growing superpixels and dividing them on image variation. The existing analysis was not sufficient to take these properties into account so new measures of oversegmentation provide new insight into the optimum superpixel representation. As a consequence of the algorithm, it was discovered that CDS has properties that have eluded previous attempts, such as initialisation invariance and stability. The completely unsupervised nature of CDS makes them highly suitable for tasks such as application to a database containing images of unknown complexity. These new superpixel properties have allowed new applications for superpixel pre-processing to be produced. These are image segmentation; image compression; scene classification; and focus detection. In addition, a new method of objectively analysing regions of focus has been developed using Light-Field photography.

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More information

Published date: March 2013
Organisations: University of Southampton, Electronics & Computer Science

Identifiers

Local EPrints ID: 351734
URI: http://eprints.soton.ac.uk/id/eprint/351734
PURE UUID: 953ecc46-682d-4a69-96b6-5e8f6676883f
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 01 May 2013 11:06
Last modified: 06 Jun 2018 13:18

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