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» A Probabilistic Framework for Combining Tracking Algorithms
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CVPR
2010
IEEE
12 years 3 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
ICRA
2002
IEEE
171views Robotics» more  ICRA 2002»
13 years 11 months ago
Robust Tracking and Structure from Motion with Sample Based Uncertainty Representation
Geometric reconstruction of the environment from images is critical in autonomous mapping and robot navigation. Geometric reconstruction involves feature tracking, i.e., locating ...
Peng Chang, Martial Hebert
AVSS
2009
IEEE
13 years 7 months ago
Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion
Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to th...
Carlos R. del-Blanco, Narciso N. García, Lu...
CVPR
1999
IEEE
14 years 8 months ago
Deformable Template and Distribution Mixture-Based Data Modeling for the Endocardial Contour Tracking in an Echographic Sequence
We1 present a new method to shape-based segmentation of deformable anatomical structures in medical images and validate this approach by detecting and tracking the endocardial bor...
Max Mignotte, Jean Meunier
CVPR
2007
IEEE
14 years 1 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen