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» Unsupervised learning of 3D object models from partial views
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ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
13 years 11 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
CGF
2008
125views more  CGF 2008»
13 years 5 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...
CORR
2010
Springer
237views Education» more  CORR 2010»
13 years 2 months ago
Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss
The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision ranging from robotic vision to image analysis. Our pro...
Srimal Jayawardena, Marcus Hutter, Nathan Brewer
CVPR
2010
IEEE
14 years 6 days ago
Multi-View Object Class Detection With a 3D Geometric Model
This paper presents a new approach for multi-view object class detection. Appearance and geometry are treated as separate learning tasks with different training data. Our approach...
Joerg Liebelt, Cordelia Schmid
CVPR
2009
IEEE
14 years 12 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese