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100
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CVPR
2005
IEEE
16 years 2 months ago
Using Particles to Track Varying Numbers of Interacting People
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
114
Voted
NIPS
2008
15 years 1 months ago
Particle Filter-based Policy Gradient in POMDPs
Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the bel...
Pierre-Arnaud Coquelin, Romain Deguest, Rém...
109
Voted
ICIAP
1999
ACM
15 years 4 months ago
Random Walk Approach to Image Enhancement
The paper presents a new technique of image enhancement. The described algorithm enables the suppression of noise and contrast enhancement. The interesting feature of this new alg...
Bogdan Smolka, Konrad W. Wojciechowski, Marek Szcz...
CVPR
2005
IEEE
16 years 2 months ago
Tracking Multiple Mouse Contours (without Too Many Samples)
We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob track...
Kristin Branson, Serge Belongie
CVPR
2005
IEEE
16 years 2 months ago
Hybrid Joint-Separable Multibody Tracking
Statistical models for tracking different moving bodies must be able to reason about occlusions in order to be effective. Representing the joint statistics across different bodies...
Oswald Lanz, Roberto Manduchi