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ICCCN
2007
IEEE
13 years 5 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
ICPR
2006
IEEE
14 years 6 months ago
Object Detection in Video via Particle Filters
We propose an object detection method using particle filters. Our approach estimates the probability of object presence in the current image given the history of observations up t...
Jacek Czyz
TSMC
2008
147views more  TSMC 2008»
13 years 4 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
ICCV
2005
IEEE
14 years 6 months ago
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
ICPR
2006
IEEE
14 years 6 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