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» Detecting branching structures using local Gaussian models
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CVPR
2005
IEEE
14 years 7 months ago
Spatial Priors for Part-Based Recognition Using Statistical Models
We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
ECCV
2006
Springer
14 years 7 months ago
Detecting Instances of Shape Classes That Exhibit Variable Structure
This paper proposes a method for detecting instances of shape classes that exhibit variable structure. The term "variable structure" is used to characterize shape classes...
Vassilis Athitsos, Jingbin Wang, Stan Sclaroff, Ma...
VMV
2001
113views Visualization» more  VMV 2001»
13 years 7 months ago
Fully-Automatic Branch Labelling of Voxel Vessel Structures
Today, it is possible to acquire volume representations of the vessel structures in the brain. The selfadjusting probe, a new tool introduced in a previous paper, enables semi-aut...
Jan Bruijns
ECCV
2008
Springer
14 years 7 months ago
Object Detection from Large-Scale 3D Datasets Using Bottom-Up and Top-Down Descriptors
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
ISVC
2010
Springer
13 years 4 months ago
Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape
In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the de...
Kai Cordes, Oliver Müller, Bodo Rosenhahn, J&...