A key component of Simultaneous Localization and Map** (SLAM) systems is the joint
optimization of the estimated 3D map and camera trajectory. Bundle adjustment (BA) is the …

The visual SLAM (vSLAM) is a research topic that has been develo** rapidly in recent
years, especially with the renewed interest in machine learning and, more particularly, deep …

We contribute a new pipeline for live multi-view performance capture, generating temporally
coherent high-quality reconstructions in real-time. Our algorithm supports both incremental …

In this paper, we focus on the problem of motion tracking in unknown environments using
visual and inertial sensors. We term this estimation task visual–inertial odometry (VIO), in …

Visual SLAM (simultaneous localization and map**) refers to the problem of using
images, as the only source of external information, in order to establish the position of a …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

This paper presents a method of estimating camera pose in an unknown scene. While this
has previously been attempted by adapting SLAM algorithms developed for robotic …

While the most accurate solution to off-line structure from motion (SFM) problems is
undoubtedly to extract as much correspondence information as possible and perform batch …

In this paper, we present incremental smoothing and map** (iSAM), which is a novel
approach to the simultaneous localization and map** problem that is based on fast …

We present a novel real-time monocular SLAM system which can robustly work in dynamic
environments. Different to the traditional methods, our system allows parts of the scene to be …