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IJCV
2000
180views more  IJCV 2000»
13 years 7 months ago
Probabilistic Models of Appearance for 3-D Object Recognition
We describe how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition. The model uses pro...
Arthur R. Pope, David G. Lowe
CVPR
2011
IEEE
12 years 11 months ago
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
CVPR
2010
IEEE
13 years 11 months ago
Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
This paper addresses the problem of recognizing freeform 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which depend on local informati...
Bertram Drost, Markus Ulrich, Nassir Navab, Slobod...
IJCV
2000
164views more  IJCV 2000»
13 years 7 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
CVPR
2001
IEEE
14 years 9 months ago
Local Feature View Clustering for 3D Object Recognition
There have been important recent advances in object recognition through the matching of invariant local image features. However, the existing approaches are based on matching to i...
David G. Lowe