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Found 11 papers, 3 papers with code
The Robot@Home2 dataset: A new release with improved usability tools
Released in 2017, Robot@Home is a dataset captured by a mobile robot during indoor navigation sessions in apartments.
Fast and Robust Certifiable Estimation of the Relative Pose Between Two Calibrated Cameras
This work contributes an efficient algorithm to compute the Relative Pose problem (RPp) between calibrated cameras and certify the optimality of the solution, given a set of pair-wise feature correspondences affected by noise and probably corrupted by wrong matches.
Certifiable Relative Pose Estimation
The optimality of the solution is then checked via our novel fast certifier.
Intrinsic Calibration of Depth Cameras for Mobile Robots using a Radial Laser Scanner
Depth cameras, typically in RGB-D configurations, are common devices in mobile robotic platforms given their appealing features: high frequency and resolution, low price and power requirements, among others.
Geometric-based Line Segment Tracking for HDR Stereo Sequences
In this work, we propose a purely geometrical approach for the robust matching of line segments for challenging stereo streams with severe illumination changes or High Dynamic Range (HDR) environments.
A Certifiably Globally Optimal Solution to the Non-Minimal Relative Pose Problem
Finding the relative pose between two calibrated views ranks among the most fundamental geometric vision problems.
Learning-based Image Enhancement for Visual Odometry in Challenging HDR Environments
One of the main open challenges in visual odometry (VO) is the robustness to difficult illumination conditions or high dynamic range (HDR) environments.
Convex Global 3D Registration With Lagrangian Duality
Thus, our approach allows for effectively solving the 3D registration with global optimality guarantees while running at a fraction of the time for the state-of-the-art alternative [34], based on a more computationally intensive Branch and Bound method.
An Efficient Background Term for 3D Reconstruction and Tracking With Smooth Surface Models
We present a novel strategy to shrink and constrain a 3D model, represented as a smooth spline-like surface, within the visual hull of an object observed from one or multiple views.
PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments
This paper proposes PL-SLAM, a stereo visual SLAM system that combines both points and line segments to work robustly in a wider variety of scenarios, particularly in those where point features are scarce or not well-distributed in the image.
Training a Convolutional Neural Network for Appearance-Invariant Place Recognition
In order for the network to learn the desired invariances, we train it with triplets of images selected from datasets which present a challenging variability in visual appearance.
