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...
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...
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...
— 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...
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 (...