Paper Info
Title
Snapshots: a novel local surface descriptor and matching algorithm for robust 3D surface alignment.
Abstract
In this paper, a novel local surface descriptor is proposed and applied to the problem of aligning partial views of a 3D object. The descriptor is based on taking "snapshots" of the surface over each point using a virtual camera oriented perpendicularly to the surface. This representation has the advantage of imposing minimal loss of information be robust to self-occlusions and also be very efficient to compute. Then, we describe an efficient search technique to deal with the rotation ambiguity of our representation and experimentally demonstrate the benefits of our approaches which are pronounced especially when we align views with small overlap.
Year
DOI
Venue
2007
10.1109/TPAMI.2007.1060
IEEE Trans. Pattern Anal. Mach. Intell.
Keywords
Field
DocType
feature extraction,image matching,image representation,object recognition,solid modelling,matching algorithm,robust 3D surface,surface descriptor,virtual camera,Surface matching,object recognition,partially overlapping surfaces.
Computer vision,Algorithm design,Computer science,Search engine indexing,Fourier transform,Feature extraction,Robustness (computer science),Artificial intelligence,Ambiguity,Blossom algorithm,Cognitive neuroscience of visual object recognition
Journal
Volume
Issue
ISSN
29
7
0162-8828
Citations 
PageRank 
References 
23
0.81
20
Authors
2
Name
Order
Citations
PageRank
Sotiris Malassiotis133527.46
Michael Gerasimos Strintzis21171104.83