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» Learning for Optical Flow Using Stochastic Optimization
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ECCV
2000
Springer
14 years 9 months ago
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
ECML
2007
Springer
13 years 11 months ago
Modeling Highway Traffic Volumes
Most traffic management and optimization tasks, such as accident detection or optimal vehicle routing, require an ability to adequately model, reason about and predict irregular an...
Tomás Singliar, Milos Hauskrecht
ICPR
2002
IEEE
14 years 20 days ago
Constrained Structure and Motion Estimation from Optical Flow
Unbiased and consistent estimates of structure and motion can be obtained by least squares minimization of the differential epipolar constraint. Previous work on this subject does...
Marco Zucchelli, José Santos-Victor, Henrik...
CVPR
2010
IEEE
14 years 4 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
AAMAS
2005
Springer
14 years 1 months ago
Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems
We report on an investigation of the learning of coordination in cooperative multi-agent systems. Specifically, we study solutions that are applicable to independent agents i.e. ...
Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. ...