399 search results - page 11 / 80 » Combining Object and Feature Dynamics in Probabilistic Track... |
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
AVSS
2005
IEEE
15 years 3 months ago
2005
IEEE
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is gener...
ICCV
2001
IEEE
15 years 11 months ago
2001
IEEE
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...