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» Recognizing 3D Objects Using Photometric Invariant
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CGF
2008
125views more  CGF 2008»
14 years 9 months ago
Sparse points matching by combining 3D mesh saliency with statistical descriptors
This paper proposes new methodology for the detection and matching of salient points over several views of an object. The process is composed by three main phases. In the first st...
Umberto Castellani, Marco Cristani, Simone Fantoni...
ECCV
2008
Springer
15 years 11 months ago
View Point Tracking of Rigid Objects Based on Shape Sub-manifolds
We study the task to infer and to track the viewpoint onto a 3D rigid object by observing its image contours in a sequence of images. To this end, we consider the manifold of invar...
Christian Gosch, Ketut Fundana, Anders Heyden, Chr...
ICCV
2007
IEEE
15 years 11 months ago
Shape from Varying Illumination and Viewpoint
We address the problem of reconstructing the 3-D shape of a Lambertian surface from multiple images acquired as an object rotates under distant and possibly varying illumination. ...
Neel Joshi, David J. Kriegman
BMVC
2010
14 years 7 months ago
Back to the Future: Learning Shape Models from 3D CAD Data
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Michael Stark, Michael Goesele, Bernt Schiele
PAMI
2012
13 years 1 days ago
LDAHash: Improved Matching with Smaller Descriptors
—SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition...
Christoph Strecha, Alexander A. Bronstein, Michael...