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» Towards a local Kalman filter for visual tracking
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ICIP
2005
IEEE
14 years 8 months ago
Visual tracking using sequential importance sampling with a state partition technique
Sequential importance sampling (SIS), also known as particle filtering, has drawn increasing attention recently due to its superior performance in nonlinear and non-Gaussian dynam...
Yan Zhai, Mark B. Yeary, Joseph P. Havlicek, Jean-...
ICIP
2003
IEEE
14 years 8 months ago
Audio-visual speaker tracking with importance particle filters
We present a probabilistic method for audio-visual (AV) speaker tracking, using an uncalibrated wide-angle camera and a microphone array. The algorithm fuses 2-D object shape and ...
Daniel Gatica-Perez, Guillaume Lathoud, Iain McCow...
ISBI
2008
IEEE
14 years 7 months ago
A new detection scheme for multiple object tracking in fluorescence microscopy by joint probabilistic data association filtering
Tracking of multiple objects in biological image data is a challenging problem due largely to poor imaging conditions and complicated motion scenarios. Existing tracking algorithm...
Ihor Smal, Wiro J. Niessen, Erik H. W. Meijering
PAMI
2007
214views more  PAMI 2007»
13 years 6 months ago
Tracking Deforming Objects Using Particle Filtering for Geometric Active Contours
—Tracking deforming objects involves estimating the global motion of the object and its local deformations as a function of time. Tracking algorithms using Kalman filters or part...
Yogesh Rathi, Namrata Vaswani, Allen Tannenbaum, A...
MICCAI
2009
Springer
14 years 8 months ago
Two-Tensor Tractography Using a Constrained Filter
We describe a technique to simultaneously estimate a weighted, positive-definite multi-tensor fiber model and perform tractography. Existing techniques estimate the local fiber ori...
James G. Malcolm, Martha Elizabeth Shenton, Yoge...