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.