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» The Dark Side of Object Learning: Learning Objects
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IROS
2008
IEEE
113views Robotics» more  IROS 2008»
15 years 11 months ago
Motion recognition and generation by combining reference-point-dependent probabilistic models
— This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned usin...
Komei Sugiura, Naoto Iwahashi
DAGM
2008
Springer
15 years 6 months ago
A Probabilistic Segmentation Scheme
We propose a probabilistic segmentation scheme, which is widely applicable to some extend. Besides the segmentation itself our model incorporates object specific shading. Dependent...
Dmitrij Schlesinger, Boris Flach
CLA
2007
15 years 6 months ago
Concept Analysis on Structured, Multi-valued and Incomplete Data
This paper presents an approach to Concept Analysis of structured, multivalued and incomplete data currently present in life science knowledge bases. We are concerned with tree str...
David Grosser, Henri Ralambondrainy
ECCV
2004
Springer
16 years 6 months ago
Reliable Fiducial Detection in Natural Scenes
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laborator...
David Claus, Andrew W. Fitzgibbon
ICIP
2006
IEEE
16 years 6 months ago
Image Manifold Interpolation using Free-Form Deformations
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...
Richard Souvenir, Qilong Zhang, Robert Pless