AuthorsGollaz Morales, Jose Alejandro
AdvisorsVigneron, Antoine E.
Permanent link to this recordhttp://hdl.handle.net/10754/248714
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AbstractMeasuring visual closeness of 3-D models is an important issue for different problems and there is still no standardized metric or algorithm to do it. The normal of a surface plays a vital role in the shading of a 3-D object. Motivated by this, we developed two applications to measure visualcloseness, introducing normal difference as a parameter in a weighted metric in Metro’s sampling approach to obtain the maximum and mean distance between 3-D models using 3-D and 6-D correspondence search structures. A visual closeness metric should provide accurate information on what the human observers would perceive as visually close objects. We performed a validation study with a group of people to evaluate the correlation of our metrics with subjective perception. The results were positive since the metrics predicted the subjective rankings more accurately than the Hausdorff distance.
CitationGollaz Morales, J. A. (2012). Measuring Visual Closeness of 3-D Models. KAUST Research Repository. https://doi.org/10.25781/KAUST-3GVS4