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CVPR
2010
IEEE
15 years 5 months ago
A probabilistic framework for joint segmentation and tracking
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
Chad Aeschliman, Johnny Park, Avinash C. Kak
DAGM
1998
Springer
15 years 9 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
CCE
2005
15 years 4 months ago
Monitoring process transitions by Kalman filtering and time-series segmentation
The analysis of historical process data of technological systems plays important role in process monitoring, modelling and control. Time-series segmentation algorithms are often u...
Balazs Feil, János Abonyi, Sandor Z. N&eacu...
ECCV
2000
Springer
16 years 6 months ago
Non-parametric Model for Background Subtraction
Abstract. Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the sc...
Ahmed M. Elgammal, David Harwood, Larry S. Davis
CVPR
2010
IEEE
15 years 3 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang