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IPMI
2007
Springer
14 years 8 months ago
Geometrically Proper Models in Statistical Training
In deformable model segmentation, the geometric training process plays a crucial role in providing shape statistical priors and appearance statistics that are used as likelihoods. ...
Qiong Han, Derek Merck, Josh Levy, Christina Villa...
ICCV
2011
IEEE
12 years 7 months ago
Superpixel Tracking
While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion,...
Shu Wang, Huchuan Lu, Fan Yang, Ming-Hsuan Yang
ICCV
2005
IEEE
14 years 1 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic
PAMI
2010
205views more  PAMI 2010»
13 years 6 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
NN
2002
Springer
161views Neural Networks» more  NN 2002»
13 years 7 months ago
AANN: an alternative to GMM for pattern recognition
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
B. Yegnanarayana, S. P. Kishore