A GPU parallel approach improving the density of patch based multi-view stereo reconstruction
Haines, Benjamin A. (2016) A GPU parallel approach improving the density of patch based multi-view stereo reconstruction. PhD thesis, University of Nottingham.
Multi-view stereo is the process of recreating three-dimensional data from a set of two or more images of a scene. The ability to acquire 3D data from 2D images is a core concept in computer vision with wide-ranging applications throughout areas such as 3D printing, robotics, recognition, navigation and a vast number of other fields. While 3D reconstruction has been increasingly well studied over the past decades, it is only with the recent evolution of CPU and GPU technologies that practical implementations, able to accurately, robustly and efficiently capture 3D data of photographed objects have begun to emerge. Whilst current research has been shown to perform well under specific circumstances and for a subset of objects, there are still many practical and implementary issues that remain an open problem for these techniques. Most notably, the ability to robustly reconstruct objects from sparse image sets or objects with low texture.
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