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Publication
200views
12 years 3 months ago
Tracking Endocardial Motion via Multiple Model Filtering of Distribution Cut
Tracking heart motion plays an essential role in the diagnosis of cardiovascular diseases. As such, accurate characterization of dynamic behavior of the left ventricle (LV) is esse...
Kumaradevan Punithakumar, Ismail Ben Ayed, Ali Isl...
IJCV
2000
161views more  IJCV 2000»
13 years 4 months ago
Probabilistic Detection and Tracking of Motion Boundaries
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Michael J. Black, David J. Fleet
WACV
2005
IEEE
13 years 10 months ago
Persistent Objects Tracking Across Multiple Non Overlapping Cameras
We present an approach for persistent tracking of moving objects observed by non-overlapping and moving cameras. Our approach robustly recovers the geometry of non-overlapping vie...
Jinman Kang, Isaac Cohen, Gérard G. Medioni
ECCV
2008
Springer
14 years 6 months ago
A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
Wei Du, Justus H. Piater
TIP
2010
141views more  TIP 2010»
12 years 11 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina