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ICCV
2011
IEEE
13 years 9 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
58
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ICML
2008
IEEE
15 years 10 months ago
Tailoring density estimation via reproducing kernel moment matching
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...
Alex J. Smola, Arthur Gretton, Bernhard Schöl...
CVPR
2010
IEEE
15 years 5 months ago
Locally-Parametric Pictorial Structures
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
Benjamin Sapp, Chris Jordan, Ben Taskar
ICCV
2009
IEEE
16 years 2 months ago
Bayesian selection of scaling laws for motion modeling in images
Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
VLSM
2005
Springer
15 years 3 months ago
Uncertainty-Driven Non-parametric Knowledge-Based Segmentation: The Corpus Callosum Case
Abstract. In this paper we propose a novel variational technique for the knowledge based segmentation of two dimensional objects. One of the elements of our approach is the use of ...
Maxime Taron, Nikos Paragios, Marie-Pierre Jolly