Object Detection for Robotic Applications Using Perceptual Organization in 3D
Abstract
Object segmentation of unknown objects with arbitrary shape in cluttered scenes is still a challenging task in computer vision. A framework is introduced to segment RGB-D images where data is processed in a hierarchical fashion. After pre-segmentation and parametrization of surface patches, support vector machines are used to learn the importance of relations between these patches. The relations are derived from perceptual grouping principles. The proposed framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. Furthermore, the problem of segmenting partially occluded objects is tackled.
- Citation
- BibTeX
Richtsfeld, A., Zillich, M. & Vincze, M.,
(2015).
Object Detection for Robotic Applications Using Perceptual Organization in 3D.
KI - Künstliche Intelligenz: Vol. 29, No. 1.
Springer.
(S. 95-99).
DOI: 10.1007/s13218-014-0339-7
@article{mci/Richtsfeld2015,
author = {Richtsfeld, Andreas AND Zillich, Michael AND Vincze, Markus},
title = {Object Detection for Robotic Applications Using Perceptual Organization in 3D},
journal = {KI - Künstliche Intelligenz},
volume = {29},
number = {1},
year = {2015},
,
pages = { 95-99 } ,
doi = { 10.1007/s13218-014-0339-7 }
}
author = {Richtsfeld, Andreas AND Zillich, Michael AND Vincze, Markus},
title = {Object Detection for Robotic Applications Using Perceptual Organization in 3D},
journal = {KI - Künstliche Intelligenz},
volume = {29},
number = {1},
year = {2015},
,
pages = { 95-99 } ,
doi = { 10.1007/s13218-014-0339-7 }
}
Sollte hier kein Volltext (PDF) verlinkt sein, dann kann es sein, dass dieser aus verschiedenen Gruenden (z.B. Lizenzen oder Copyright) nur in einer anderen Digital Library verfuegbar ist. Versuchen Sie in diesem Fall einen Zugriff ueber die verlinkte DOI: 10.1007/s13218-014-0339-7
Haben Sie fehlerhafte Angaben entdeckt? Sagen Sie uns Bescheid: Send Feedback
More Info
ISSN: 1610-1987
xmlui.MetaDataDisplay.field.date: 2015
Content Type: Text/Journal Article