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» A Computational Framework for Handling Motion
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CVPR
2005
IEEE
14 years 11 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
EMMCVPR
2011
Springer
12 years 9 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen
ICIP
2007
IEEE
14 years 11 months ago
Fundamental Matrix Estimation Without Prior Match
This paper presents a probabilistic framework for computing correspondences and fundamental matrix in the structure from motion problem. Inspired by Moisan and Stival [1], we sugg...
Frédéric Sur, Marie-Odile Berger, Ni...
ISBI
2008
IEEE
14 years 10 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
ICRA
2008
IEEE
185views Robotics» more  ICRA 2008»
14 years 3 months ago
Humanoid teleoperation for whole body manipulation
— We present results of successful telemanipulation of large, heavy objects by a humanoid robot. Using a single joystick the operator controls walking and whole body manipulation...
Mike Stilman, Koichi Nishiwaki, Satoshi Kagami