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» Learning 3D mesh segmentation and labeling
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SIGGRAPH
2010
ACM
13 years 8 months ago
Learning 3D mesh segmentation and labeling
Evangelos Kalogerakis, Aaron Hertzmann, Karan Sing...
3DOR
2008
13 years 7 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
ICPR
2000
IEEE
13 years 9 months ago
Segmentation and Surface Characterization of Arbitrary 3D Meshes for Object Reconstruction and Recognition
Polygonal models are the most common representation of structured 3D data in computer graphics, pattern recognition and machine vision. The method presented here automatically ide...
Georgios Papaioannou, Evaggelia-Aggeliki Karabassi...
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
13 years 11 months ago
Model-based and learned semantic object labeling in 3D point cloud maps of kitchen environments
Abstract— We report on our experiences regarding the acquisition of hybrid Semantic 3D Object Maps for indoor household environments, in particular kitchens, out of sensed 3D poi...
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow...
CVPR
2005
IEEE
14 years 6 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...