Search Results for author:
Found 14 papers, 6 papers with code
LightDepth: Single-View Depth Self-Supervision from Illumination Decline
However, there are scenarios, especially in medicine in the case of endoscopies, where such data cannot be obtained.
ColonMapper: topological mapping and localization for colonoscopy
We propose a topological mapping and localization system able to operate on real human colonoscopies, despite significant shape and illumination changes.
Photometric single-view dense 3D reconstruction in endoscopy
We validate our method on simulated colonoscopies, obtaining a mean error of 7% on depth estimation, which is below 3 mm on average.
Reuse your features: unifying retrieval and feature-metric alignment
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.
Direct and Sparse Deformable Tracking
Current approaches use a template-based deformable tracking to recover the camera pose and the deformation of the map.
Endo-Depth-and-Motion: Reconstruction and Tracking in Endoscopic Videos using Depth Networks and Photometric Constraints
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.
ORBSLAM-Atlas: a robust and accurate multi-map system
We also show the robustness and capability of our system to deal with dynamic scenes, quantitatively in the EuRoC datasets and qualitatively in a densely populated corridor where camera occlusions and tracking losses are frequent.
Fast and Robust Initialization for Visual-Inertial SLAM
Visual-inertial SLAM (VI-SLAM) requires a good initial estimation of the initial velocity, orientation with respect to gravity and gyroscope and accelerometer biases.
Robotics
DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequences
In our experiments, DefSLAM processes close-up sequences of deforming scenes, both in a laboratory controlled experiment and in medical endoscopy sequences, producing accurate 3D models of the scene with respect to the moving camera.
SLAM based Quasi Dense Reconstruction For Minimally Invasive Surgery Scenes
In this paper, a quasi dense reconstruction algorithm of surgical scene is proposed.
ORBSLAM-based Endoscope Tracking and 3D Reconstruction
It is our first contribution to exploit ORBSLAM, one of the best performing monocular SLAM algorithms, to estimate both of the endoscope location, and 3D structure of the surgical scene.
Real-time Monocular Object SLAM
We present a real-time object-based SLAM system that leverages the largest object database to date.
ORB-SLAM: a Versatile and Accurate Monocular SLAM System
This paper presents ORB-SLAM, a feature-based monocular SLAM system that operates in real time, in small and large, indoor and outdoor environments.
