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118
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CVPR
1999
IEEE
16 years 2 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
88
Voted
CVPR
2006
IEEE
16 years 2 months ago
Scalable Monocular SLAM
Localization and mapping in unknown environments becomes more difficult as the complexity of the environment increases. With conventional techniques, the cost of maintaining estim...
Ethan Eade, Tom Drummond
76
Voted
ICCV
2005
IEEE
16 years 2 months ago
Avoiding the "Streetlight Effect": Tracking by Exploring Likelihood Modes
Classic methods for Bayesian inference effectively constrain search to lie within regions of significant probability of the temporal prior. This is efficient with an accurate dyna...
David Demirdjian, Leonid Taycher, Gregory Shakhnar...
ICCV
2003
IEEE
16 years 2 months ago
Video Google: A Text Retrieval Approach to Object Matching in Videos
We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set...
Josef Sivic, Andrew Zisserman
101
Voted
ECCV
2006
Springer
16 years 2 months ago
Density Estimation Using Mixtures of Mixtures of Gaussians
In this paper we present a new density estimation algorithm using mixtures of mixtures of Gaussians. The new algorithm overcomes the limitations of the popular Expectation Maximiza...
Wael Abd-Almageed, Larry S. Davis