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» Probabilistic Modeling and Recognition of 3-D Objects
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CVPR
2011
IEEE
12 years 10 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
WACV
2005
IEEE
14 years 16 days ago
3D Recognition and Segmentation of Objects in Cluttered Scenes
In this paper we present a novel view point independent range image segmentation and recognition approach. We generate a library of 3D models off-line and represent each model wit...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
MVA
1990
137views Computer Vision» more  MVA 1990»
13 years 8 months ago
Relaxation Based Modeling and Recognition of 3D Surfaces from Range Data
Modeling and recognition of 3D objects by surface is an important problem in machine vision. Given a large number of range data points of an object surface, we present a relaxatio...
Chang Y. Choo, Nasser M. Nasrabadi, William I. Kwa...
CLOR
2006
13 years 10 months ago
What and Where: 3D Object Recognition with Accurate Pose
Abstract. Many applications of 3D object recognition, such as augmented reality or robotic manipulation, require an accurate solution for the 3D pose of the recognized objects. Thi...
Iryna Gordon, David G. Lowe
ICIP
2001
IEEE
14 years 8 months ago
Use of a probabilistic shape model for non-linear registration of 3D scattered data
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...
Isabelle Corouge, Christian Barillot