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ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling
94
Voted
CVPR
2006
IEEE
16 years 1 months ago
Real-Time Visual SLAM with Resilience to Erratic Motion
Simultaneous localisation and mapping using a single camera becomes difficult when erratic motions violate predictive motion models. This problem needs to be addressed when visual...
Mark Pupilli, Andrew Calway
ETFA
2008
IEEE
15 years 6 months ago
3D-based monocular SLAM for mobile agents navigating in indoor environments
This paper presents a novel algorithm for 3D depth estimation using a particle filter (PFDE - Particle Filter Depth Estimation) in a monocular vSLAM (Visual Simultaneous Localiza...
Dejan Pangercic, Radu Bogdan Rusu, Michael Beetz
ICRA
2006
IEEE
138views Robotics» more  ICRA 2006»
15 years 5 months ago
Evaluation of Algorithms for bearing-only SLAM
— An important milestone for building affordable robots that can become widely popular is to address robustly the Simultaneous Localization and Mapping (SLAM) problem with inexpe...
Kostas E. Bekris, Max Glick, Lydia E. Kavraki
CVPR
2010
IEEE
13 years 9 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu