UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The Atlas Structure of Images

Griffin, LD; (2019) The Atlas Structure of Images. IEEE Transactions on Pattern Analysis and Machine Intelligence , 41 (1) pp. 234-245. 10.1109/TPAMI.2017.2777856. Green open access

[thumbnail of Griffin_Atlas_Structure_Images_AAM.pdf]
Preview
Text
Griffin_Atlas_Structure_Images_AAM.pdf - Accepted Version

Download (2MB) | Preview

Abstract

Many operations of vision require image regions to be isolated and inter-related. This is challenging when they are different in detail and extent. Practical methods of Computer Vision approach this through the tools of downsampling, pyramids, cropping and patches. In this paper we develop an ideal geometric structure for this, compatible with the existing scale space model of image measurement. Its elements are apertures which view the image like fuzzy-edged portholes of frosted glass. We establish containment and cause/effect relations between apertures, and show that these link them into cross-scale atlases. Atlases formed of Gaussian apertures are shown to be a continuous version of the image pyramid used in Computer Vision, and allow various types of image description to naturally be expressed within their framework. We show that views through Gaussian apertures are approximately equivalent to the jets of derivative of Gaussian filter responses that form part of standard Scale Space theory. This supports a view of the simple cells of mammalian V1 as implementing a system of local views of the retinal image of varying extent and resolution. As a worked example we develop a keypoint descriptor scheme that outperforms previous schemes that do not make use of learning.

Type: Article
Title: The Atlas Structure of Images
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TPAMI.2017.2777856
Publisher version: https://doi.org/10.1109/TPAMI.2017.2777856
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Image Analysis, Image Representation, Image Resolution, Gaussian Derivatives, Filter Steering, Keypoints
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10043143
Downloads since deposit
135Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item