Authors:
Nader H. Aldeeb
and
Olaf Hellwich
Affiliation:
Technische Universität Berlin, Germany
Keyword(s):
Point Cloud, Hole Detection, Hole Classification, Hole Filling, Surface Reconstruction, Textureless Surfaces, Segmentation with Graph Cuts.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Geometry and Modeling
;
Image and Video Analysis
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Software Engineering
;
Stereo Vision and Structure from Motion
Abstract:
Structure from Motion (SfM) is the most popular technique behind 3D image reconstruction. It is mainly
based on matching features between multiple views of the target object. Therefore, it gives good results only
if the target object has enough texture on its surface. If not, virtual holes are caused in the estimated models.
But, not all holes that appear in the estimated model are virtual, i.e. correspond to a failure of the
reconstruction. There could be a real physical hole in the structure of the target object being reconstructed.
This presents ambiguity when applying a hole-filling algorithm. That is, which hole should be filled and
which must be left as it is. In this paper, we first propose a simple approach for the detection of holes in
point sets. Then we investigate two different measures for automatic classification of these detected holes in
point sets. According to our knowledge, hole-classification has not been addressed beforehand. Experiments
showed that all holes in
3D models are accurately identified and classified.
(More)