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The dense matching method based on ASIFT is an efficient method for establishing correspondence between arbitrarily-selected points within two widely-separated views. Its main strength is that it is capable of finding a correspondence, even for pixels, within an area with certain uniform properties, such as similar colours and/or textures. The basic version of this method during its segmentation step presupposes that the segmented regions meet a coplanarity criterion, which is an unattainable requirement for the majority of segmentation methods. Therefore in the upgraded version of this method…mehr

Produktbeschreibung
The dense matching method based on ASIFT is an efficient method for establishing correspondence between arbitrarily-selected points within two widely-separated views. Its main strength is that it is capable of finding a correspondence, even for pixels, within an area with certain uniform properties, such as similar colours and/or textures. The basic version of this method during its segmentation step presupposes that the segmented regions meet a coplanarity criterion, which is an unattainable requirement for the majority of segmentation methods. Therefore in the upgraded version of this method we have introduced a step for the adaptive adjustment of obtained segmentation results. This step is based on a 3D reconstruction of the initial corresponding points and a search for the minimal number of planes within the 3D space to which these points belong. The dense matching method based on ASIFT can establish correspondence in general situations. The only requirement is that the observed objects should have planar surfaces. Method accuracy was proven by experiments on images acquired from different construction sites and other residential buildings.
Autorenporträt
Peter Podbreznik received his Ph.D. degree in Computer Science from the University of Maribor, Slovenia. Currently he works as Assistant Professor at Faculty of Civil Engineering at University of Maribor. His research interests are construction information technologies, signal and image processing, computer vision and biomedicine.