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- W3180789677 abstract "Three-dimensional models are important products of measurement systems in a variety of applications such as archaeology, medicine, architecture and engineering. In order to be appropriate to the end user, such object models must comply with certain accuracy standards. To achieve both accuracy and object coverage with a close range photogrammetric approach often requires a convergent image network in combination with retro reflective targets or some form of projected pattern. Retro-reflective targets alone can only provide sparse data. However, by optimising image acquisition to record both targets and natural surface texture information, proven high accuracy retro reflective target image measurement can be combined with a wealth of automated image analysis algorithms developed by both photogrammetric and machine vision communities.This research is focused on combining photogrammetric and machine vision measurement techniques, through an automated model generation tool based upon dynamic Delaunay triangulation. The model is initialised by a sparse set of retro reflective targets, which form a Delaunay triangulation network known both in image and object space. The original triangles are densified by a multi-image approach, which uses both the image geometry information (through constrained epipolar lines) as well as radiometric properties (patch matching) within relevant triangles. The triangle network is further constrained by edge boundary information to follow the surface of individual objects in the imaged scene. Each set of points produced at various stages of the process is tagged with a unique flag that corresponds to a level of accuracy, determined either through multi-photo intersection or in a more general case through bundle adjustment." @default.
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- W3180789677 date "2001-01-01" @default.
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- W3180789677 title "Towards the automated extraction of accurate 3D models from close range photogrammetric networks" @default.
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