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CVPR
2004
IEEE
14 years 8 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...
FGR
2006
IEEE
262views Biometrics» more  FGR 2006»
14 years 23 days ago
Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images
This paper presents the application of a kernel particle filter for 3D body tracking in a video stream acquired from a single uncalibrated camera. Using intensity-based and color...
Joachim Schmidt, Jannik Fritsch, Bogdan Kwolek
ICCV
2007
IEEE
13 years 8 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
NIPS
2003
13 years 8 months ago
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Liva Ralaivola, Florence d'Alché-Buc
ICIP
2005
IEEE
14 years 8 months ago
The impulse responses of block shift-invariant systems and their use for demosaicing algorithms
Shift-invariant linear algorithms can be described completely by the algorithm's response to an impulse input. The so called impulse response can be used as filter kernels wh...
Yacov Hel-Or