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» Tracking Discontinuous Motion Using Bayesian Inference
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SCVMA
2004
Springer
15 years 3 months ago
Comparison of Edge-Driven Algorithms for Model-Based Motion Estimation
3D-model-based tracking offers one possibility to explicate the manner in which spatial coherence can be exploited for the analysis of image sequences. Two seemingly different ap...
Hendrik Dahlkamp, Artur Ottlik, Hans-Hellmut Nagel
ACCV
2006
Springer
15 years 3 months ago
Online Updating Appearance Generative Mixture Model for Meanshift Tracking
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks object by maximizing the similarity betwe...
Jilin Tu, Hai Tao, Thomas S. Huang
SSIAI
2000
IEEE
15 years 2 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
15 years 11 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black
ICPR
2002
IEEE
15 years 10 months ago
4-D Voting for Matching, Densification and Segmentation into Motion Layers
* We present a novel approach for grouping from motion, based on a 4-D Tensor Voting computational framework. From sparse point tokens in two frames we recover the dense velocity f...
Gérard G. Medioni, Mircea Nicolescu