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ICCV
2007
IEEE
14 years 7 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
IWCM
2004
Springer
13 years 10 months ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
JUCS
2010
265views more  JUCS 2010»
13 years 3 months ago
A General Framework for Multi-Human Tracking using Kalman Filter and Fast Mean Shift Algorithms
: The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human track...
Ahmed Ali, Kenji Terada
BMVC
1998
13 years 6 months ago
Detection and Tracking of Very Small Low Contrast Objects
We present a Kalman tracking algorithm that can track a number of very small, low contrast objects through an image sequence taken from a static camera. The issues that we have ad...
D. Davies, Phil L. Palmer, Majid Mirmehdi
CLOR
2006
13 years 8 months ago
The Trace Model for Object Detection and Tracking
We introduce a stochastic model to characterize the online computational process of an object recognition system based on a hierarchy of classifiers. The model is a graphical netwo...
Sachin Gangaputra, Donald Geman