65 search results - page 2 / 13 » Unsupervised learning of probabilistic object models (POMs) ... |
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
CVPR
2003
IEEE
14 years 6 months ago
2003
IEEE
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
ACCV
2010
Springer
12 years 11 months ago
2010
Springer
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
ICCV
2005
IEEE
14 years 6 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Phoneme segmentation is a fundamental problem in many speech recognition and synthesis studies. Unsupervised phoneme segmentation assumes no knowledge on linguistic contents and a...