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» Extended Object Tracking Using Monte Carlo Methods
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CVPR
2009
IEEE
16 years 7 months ago
Tracking of a Non-Rigid Object via Patch-based Dynamic Appearance Modeling and Adaptive Basin Hopping Monte Carlo Sampling
We propose a novel tracking algorithm for the target of which geometric appearance changes drastically over time. To track it, we present a local patch-based appearance model and p...
Junseok Kwon (Seoul National University), Kyoung M...
ICASSP
2011
IEEE
14 years 6 months ago
Particle algorithms for filtering in high dimensional state spaces: A case study in group object tracking
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
Lyudmila Mihaylova, Avishy Carmi
ICPR
2006
IEEE
16 years 3 months ago
An integrated Monte Carlo data association framework for multi-object tracking
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
117
Voted
CVPR
2007
IEEE
15 years 8 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
134
Voted
IVC
2007
89views more  IVC 2007»
15 years 2 months ago
Sequential Monte Carlo tracking by fusing multiple cues in video sequences
This paper presents visual cues for object tracking in video sequences using particle filtering. A consistent histogram-based framework is developed for the analysis of colour, e...
Paul Brasnett, Lyudmila Mihaylova, David R. Bull, ...