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CVPR
2004
IEEE
14 years 9 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
KES
2007
Springer
14 years 1 months ago
Fuzzy Adaptive Particle Filter for Localization of a Mobile Robot
Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of localization are due to uncertainties in the modelin...
Young-Joong Kim, Chan-Hee Won, Jung-Min Pak, Myo-T...
TSMC
2008
147views more  TSMC 2008»
13 years 7 months ago
Tracking of Multiple Targets Using Online Learning for Reference Model Adaptation
Recently, much work has been done in multiple ob-4 ject tracking on the one hand and on reference model adaptation5 for a single-object tracker on the other side. In this paper, we...
Franz Pernkopf
ICPR
2006
IEEE
14 years 8 months ago
Adaptive Weighting of Local Classifiers by Particle Filter
This paper presents adaptive weighting method for combining local classifiers by particle filter. In recent years, the effectiveness of combination of local classifiers (features)...
Kazuhiro Hotta
CVPR
2005
IEEE
14 years 1 months ago
Online Selecting Discriminative Tracking Features Using Particle Filter
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Jianyu Wang, Xilin Chen, Wen Gao