Visual Odometry

97 papers with code • 0 benchmarks • 21 datasets

Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.

Source: Bi-objective Optimization for Robust RGB-D Visual Odometry

Libraries

Use these libraries to find Visual Odometry models and implementations

Most implemented papers

The Double Sphere Camera Model

ethz-asl/kalibr 24 Jul 2018

We evaluate the model using a calibration dataset with several different lenses and compare the models using the metrics that are relevant for Visual Odometry, i. e., reprojection error, as well as computation time for projection and unprojection functions and their Jacobians.

ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras

raulmur/ORB_SLAM2 20 Oct 2016

We present ORB-SLAM2 a complete SLAM system for monocular, stereo and RGB-D cameras, including map reuse, loop closing and relocalization capabilities.

DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks

ChiWeiHsiao/DeepVO-pytorch 25 Sep 2017

This paper presents a novel end-to-end framework for monocular VO by using deep Recurrent Convolutional Neural Networks (RCNNs).

The TUM VI Benchmark for Evaluating Visual-Inertial Odometry

EnriqueSolarte/robust_360_8PA 17 Apr 2018

For trajectory evaluation, we also provide accurate pose ground truth from a motion capture system at high frequency (120 Hz) at the start and end of the sequences which we accurately aligned with the camera and IMU measurements.

A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors

HKUST-Aerial-Robotics/VINS-Fusion 11 Jan 2019

We validate the performance of our system on public datasets and through real-world experiments with multiple sensors.

Towards Better Generalization: Joint Depth-Pose Learning without PoseNet

B1ueber2y/TrianFlow CVPR 2020

In this work, we tackle the essential problem of scale inconsistency for self-supervised joint depth-pose learning.

PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments

rubengooj/pl-slam 26 May 2017

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.

Stereo relative pose from line and point feature triplets

alexandervakhitov/sego-paper-code ECCV 2018

In this work, we present two minimal solvers for the stereo relative pose.

Direct Sparse Odometry

JakobEngel/dso 9 Jul 2016

We propose a novel direct sparse visual odometry formulation.

Reducing Drift in Visual Odometry by Inferring Sun Direction Using a Bayesian Convolutional Neural Network

utiasSTARS/sun-bcnn-vo 20 Sep 2016

We present a method to incorporate global orientation information from the sun into a visual odometry pipeline using only the existing image stream, where the sun is typically not visible.