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» A Probabilistic Framework for Combining Tracking Algorithms
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SSIAI
2000
IEEE
13 years 11 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
CVPR
2004
IEEE
14 years 9 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
TCSV
2008
107views more  TCSV 2008»
13 years 7 months ago
Person Surveillance Using Visual and Infrared Imagery
This paper presents a methodology for analyzing multimodal and multiperspective systems for person surveillance. Using an experimental testbed consisting of two color and two infra...
Stephen J. Krotosky, Mohan M. Trivedi
ICCV
2009
IEEE
13 years 5 months ago
Probabilistic occlusion boundary detection on spatio-temporal lattices
In this paper, we present an algorithm for occlusion boundary detection. The main contribution is a probabilistic detection framework defined on spatio-temporal lattices, which en...
Mehmet Emre Sargin, Luca Bertelli, Bangalore S. Ma...
ICIP
2009
IEEE
14 years 8 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...