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» Multiple Object Tracking with Kernel Particle Filter
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CDC
2008
IEEE
143views Control Systems» more  CDC 2008»
13 years 11 months ago
Particle filtering using multiple cross-correlations for tracking occluded objects in cluttered scenes
— This paper is concerned with the tracking of partially or entirely occluded objects in a video sequence. We propose certain modifications to the template matching approach, whi...
Arie Nakhmani, Allen Tannenbaum
IPMI
2007
Springer
14 years 6 months ago
Rao-Blackwellized Marginal Particle Filtering for Multiple Object Tracking in Molecular Bioimaging
Modern live cell fluorescence microscopy imaging systems, used abundantly for studying intra-cellular processes in vivo, generate vast amounts of noisy image data that cannot be pr...
Ihor Smal, Katharina Draegestein, Niels Galjart, W...
CVPR
2004
IEEE
14 years 7 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...
ICPR
2006
IEEE
14 years 6 months ago
Non-overlapping Distributed Tracking using Particle Filter
Tracking people or objects across multiple cameras is a challenging research area in visual computing especially when these cameras have non-overlapping field-of-views. The import...
Fee-Lee Lim, Tele Tan, Wilson S. Leoputra
ISBI
2008
IEEE
14 years 6 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