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Processing Sparse Panoramic Images via Space Variant Operators

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Coleman, SA, Scotney, BW and Kerr, D (2008) Processing Sparse Panoramic Images via Space Variant Operators. International Journal of Mathematical Imaging and Vision, 32 (2). pp. 349-361. [Journal article]

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DOI: 10.1007/s10851-008-0107-0

Abstract

The use of omni-directional cameras has become increasingly popular in vision systems for video surveillance and autonomous robot navigation. However, to date most of the research relating to omni-directional cameras has focussed on the design of the camera or the way in which to project the omni-directional image to a panoramic view rather than the processing of such images after capture. Typically images obtained from omni-directional cameras are transformed to sparse panoramic images that are interpolated to obtain a complete panoramic view prior to low level image processing. This interpolation presents a significant computational overhead with respect to real-time vision. We present an efficient design procedure for space variant feature extraction operators that can be applied to a sparse panoramic image and directly processes this sparse image. This paper highlights the reduction of the computational overheads of directly processing images arising from omni-directional cameras through efficient coding and storage, whilst retaining accuracy sufficient for application to real-time robot vision.

Item Type:Journal article
Keywords:Sparse images; Space variant operators; Omni-directional images
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:6858
Deposited By:Professor Bryan Scotney
Deposited On:20 Jan 2010 15:58
Last Modified:15 Jun 2011 11:08

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