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SSIAI
2000
IEEE
14 years 2 days 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
IBPRIA
2003
Springer
14 years 27 days ago
Multiple Segmentation of Moving Objects by Quasi-simultaneous Parametric Motion Estimation
Abstract. This paper presents a new framework for the motion segmentation and estimation task on sequences of two grey images without a priori information of the number of moving r...
Raúl Montoliu, Filiberto Pla
PAMI
2012
11 years 10 months ago
Fast Joint Estimation of Silhouettes and Dense 3D Geometry from Multiple Images
—We propose a probabilistic formulation of joint silhouette extraction and 3D reconstruction given a series of calibrated 2D images. Instead of segmenting each image separately i...
Kalin Kolev, Thomas Brox, Daniel Cremers
ICCV
2003
IEEE
14 years 9 months ago
Filtering Using a Tree-Based Estimator
Within this paper a new framework for Bayesian tracking is presented, which approximates the posterior distribution at multiple resolutions. We propose a tree-based representation...
Bjoern Stenger, Arasanathan Thayananthan, Philip H...
NIPS
2000
13 years 9 months ago
Learning and Tracking Cyclic Human Motion
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...