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» A General Framework for Combining Visual Trackers - The
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AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 3 days ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
VISSYM
2004
13 years 8 months ago
Generalized Distance Transforms and Skeletons in Graphics Hardware
We present a framework for computing generalized distance transforms and skeletons of two-dimensional objects using graphics hardware. Our method is based on the concept of footpr...
Robert Strzodka, Alexandru Telea
PAMI
2002
150views more  PAMI 2002»
13 years 7 months ago
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
Decomposing video frames into coherent two-dimensional motion layers is a powerful method for representing videos. Such a representation provides an intermediate description that e...
Hai Tao, Harpreet S. Sawhney, Rakesh Kumar
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
13 years 5 months ago
Ensemble-Vis: A Framework for the Statistical Visualization of Ensemble Data
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...