Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Montiel, J. M. M"'
Autor:
Rodríguez-Puigvert, Javier, Batlle, Víctor M., Montiel, J. M. M., Martinez-Cantin, Ruben, Fua, Pascal, Tardós, Juan D., Civera, Javier
Single-view depth estimation can be remarkably effective if there is enough ground-truth depth data for supervised training. However, there are scenarios, especially in medicine in the case of endoscopies, where such data cannot be obtained. In such
Externí odkaz:
http://arxiv.org/abs/2308.10525
In this paper we present NR-SLAM, a novel non-rigid monocular SLAM system founded on the combination of a Dynamic Deformation Graph with a Visco-Elastic deformation model. The former enables our system to represent the dynamics of the deforming envir
Externí odkaz:
http://arxiv.org/abs/2308.04036
We propose a topological mapping and localization system able to operate on real human colonoscopies, despite significant shape and illumination changes. The map is a graph where each node codes a colon location by a set of real images, while edges r
Externí odkaz:
http://arxiv.org/abs/2305.05546
Visual SLAM inside the human body will open the way to computer-assisted navigation in endoscopy. However, due to space limitations, medical endoscopes only provide monocular images, leading to systems lacking true scale. In this paper, we exploit th
Externí odkaz:
http://arxiv.org/abs/2204.09083
Monocular SLAM in deformable scenes will open the way to multiple medical applications like computer-assisted navigation in endoscopy, automatic drug delivery or autonomous robotic surgery. In this paper we propose a novel method to simultaneously tr
Externí odkaz:
http://arxiv.org/abs/2204.08309
Autor:
Morlana, Javier, Montiel, J. M. M.
We propose a compact pipeline to unify all the steps of Visual Localization: image retrieval, candidate re-ranking and initial pose estimation, and camera pose refinement. Our key assumption is that the deep features used for these individual tasks s
Externí odkaz:
http://arxiv.org/abs/2204.06292
Deformable Monocular SLAM algorithms recover the localization of a camera in an unknown deformable environment. Current approaches use a template-based deformable tracking to recover the camera pose and the deformation of the map. These template-base
Externí odkaz:
http://arxiv.org/abs/2109.07370
Estimating a scene reconstruction and the camera motion from in-body videos is challenging due to several factors, e.g. the deformation of in-body cavities or the lack of texture. In this paper we present Endo-Depth-and-Motion, a pipeline that estima
Externí odkaz:
http://arxiv.org/abs/2103.16525
We propose ORBSLAM-Atlas, a system able to handle an unlimited number of disconnected sub-maps, that includes a robust map merging algorithm able to detect sub-maps with common regions and seamlessly fuse them. The outstanding robustness and accuracy
Externí odkaz:
http://arxiv.org/abs/1908.11585
Publikováno v:
C. Campos, M. Jos\'e M.M. and J. D. Tard\'os, "Fast and Robust Initialization for Visual-Inertial SLAM," 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 1288-1294
Visual-inertial SLAM (VI-SLAM) requires a good initial estimation of the initial velocity, orientation with respect to gravity and gyroscope and accelerometer biases. In this paper we build on the initialization method proposed by Martinelli and exte
Externí odkaz:
http://arxiv.org/abs/1908.10653