Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.561935
Title: Completing unknown portions of 3D scenes by 3D visual propagation
Author: Breckon, Toby P.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2006
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Abstract:
As the requirement for more realistic 3D environments is pushed forward by the computer {graphics | movie | simulation | games} industry, attention turns away from the creation of purely synthetic, artist derived environments towards the use of real world captures from the 3D world in which we live. However, common 3D acquisition techniques, such as laser scanning and stereo capture, are realistically only 2.5D in nature - such that the backs and occluded portions of objects cannot be realised from a single uni-directional viewpoint. Although multi-directional capture has existed for sometime, this incurs additional temporal and computational cost with no existing guarantee that the resulting acquisition will be free of minor holes, missing surfaces and alike. Drawing inspiration from the study of human abilities in 3D visual completion, we consider the automated completion of these hidden or missing portions in 3D scenes originally acquired from 2.5D (or 3D) capture. We propose an approach based on the visual propagation of available scene knowledge from the known (visible) scene areas to these unknown (invisible) 3D regions (i.e. the completion of unknown volumes via visual propagation - the concept of volume completion). Our proposed approach uses a combination of global surface fitting, to derive an initial underlying geometric surface completion, together with a 3D extension of nonparametric texture synthesis in order to provide the propagation of localised structural 3D surface detail (i.e. surface relief). We further extend our technique both to the combined completion of 3D surface relief and colour and additionally to hierarchical surface completion that offers both improved structural results and computational efficiency gains over our initial non-hierarchical technique. To validate the success of these approaches we present the completion and extension of numerous 2.5D (and 3D) surface examples with relief ranging in natural, man-made, stochastic, regular and irregular forms. These results are evaluated both subjectively within our definition of plausible completion and quantitatively by statistical analysis in the geometric and colour domains.
Supervisor: Fisher, Robert B. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.561935  DOI: Not available
Keywords: artificial intelligence ; computer vision ; 3D vision ; computer graphics ; surface completion ; occlusion resolution ; range data ; stereo vision
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