THESIS
2020
xi, 36 pages : illustrations ; 30 cm
Abstract
3D reconstruction applications have been constantly developed in the past decades in aspects
including accuracy, efficiency and robustness. In the reconstruction pipeline, structure from motion
(SfM) is a photogrammetric approach to calculate 3D point positions and camera poses based
on 2D images. Unqualified images, such as those under diverse illumination conditions or with
insufficient details, may lead to inadequate feature point matches and therefore cause deficiencies
in the reconstruction output. In order to further improve the quality of the result, we propose
interactive techniques, in which humans are able to supplement data required by the SfM pipeline
to refine the reconstruction.
Our proposed methods consist of two main parts. Firstly, supplementary images can be re...[
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3D reconstruction applications have been constantly developed in the past decades in aspects
including accuracy, efficiency and robustness. In the reconstruction pipeline, structure from motion
(SfM) is a photogrammetric approach to calculate 3D point positions and camera poses based
on 2D images. Unqualified images, such as those under diverse illumination conditions or with
insufficient details, may lead to inadequate feature point matches and therefore cause deficiencies
in the reconstruction output. In order to further improve the quality of the result, we propose
interactive techniques, in which humans are able to supplement data required by the SfM pipeline
to refine the reconstruction.
Our proposed methods consist of two main parts. Firstly, supplementary images can be retrieved
efficiently to enhance details in the reconstruction output. Secondly, a graphical user interface
(GUI) is improved for visualization and interactive creation of feature matches. To incorporate
new images and feature matches, additional interfaces are added to the SfM pipeline.
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