Journal ArticleDOI
CoSLAM: Collaborative Visual SLAM in Dynamic Environments
Danping Zou,Ping Tan +1 more
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TLDR
Experimental results demonstrate that the vision-based simultaneous localization and mapping in dynamic environments with multiple cameras can work robustly in highly dynamic environments and produce more accurate results in static environments.Abstract:
This paper studies the problem of vision-based simultaneous localization and mapping (SLAM) in dynamic environments with multiple cameras. These cameras move independently and can be mounted on different platforms. All cameras work together to build a global map, including 3D positions of static background points and trajectories of moving foreground points. We introduce intercamera pose estimation and intercamera mapping to deal with dynamic objects in the localization and mapping process. To further enhance the system robustness, we maintain the position uncertainty of each map point. To facilitate intercamera operations, we cluster cameras into groups according to their view overlap, and manage the split and merge of camera groups in real time. Experimental results demonstrate that our system can work robustly in highly dynamic environments and produce more accurate results in static environments.read more
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HybridEarth: Social mixed reality at planet scale
TL;DR: Using Google Street View navigable imagery and adding users' avatars to it, HybridEarth is implemented, a virtual world copy of the real world, built on top of Kiwano, a distributed infrastructure for scaling virtual worlds, designed and implemented by the team.
Enhancing 3D Visual Odometry with Single-Camera Stereo Omnidirectional Systems
TL;DR: Low-cost solutions for improving the 3D pose estimation problem of a single camera moving in an unfamiliar environment are explored by enhancing 3D Visual Odometry with Single-Camera Stereo Omnidirectional Systems.
Journal ArticleDOI
Sharing visual-inertial data for collaborative decentralized simultaneous localization and mapping
TL;DR: In this article, the authors propose three methods to share visual-inertial information, based on rigid, condensed and pruned visual inertial packets, and also propose a common collaborative SLAM architecture to organize the computation, exchange and integration of such packets.
Proceedings ArticleDOI
A Multi-Robot Collaborative Monocular SLAM Based on Semi-Direct Method
TL;DR: In this article , a semi-direct method is proposed for multi-robot cooperative visual simultaneous localization and mapping (SLAM) in complex environments, where each robot runs a direct method based visual odometry, which can both preserve their own autonomy and enable fast and robust pose tracking on local maps.
Proceedings ArticleDOI
Motion target correlation method based on structural similarity in camera array
TL;DR: A novel motion target correlation method based on structural similarity that can effectively accomplish the correlation of the same moving target between single-target and multi-target scene with high robustness is proposed.
References
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Proceedings ArticleDOI
Good features to track
Jianbo Shi,Tomasi +1 more
TL;DR: A feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world are proposed.
Proceedings ArticleDOI
Parallel Tracking and Mapping for Small AR Workspaces
Georg Klein,David W. Murray +1 more
TL;DR: A system specifically designed to track a hand-held camera in a small AR workspace, processed in parallel threads on a dual-core computer, that produces detailed maps with thousands of landmarks which can be tracked at frame-rate with accuracy and robustness rivalling that of state-of-the-art model-based systems.
Journal ArticleDOI
MonoSLAM: Real-Time Single Camera SLAM
TL;DR: The first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches is presented.
Journal ArticleDOI
Simultaneous localization and mapping: part I
TL;DR: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method.
Proceedings ArticleDOI
Real-time simultaneous localisation and mapping with a single camera
TL;DR: This work presents a top-down Bayesian framework for single-camera localisation via mapping of a sparse set of natural features using motion modelling and an information-guided active measurement strategy, in particular addressing the difficult issue of real-time feature initialisation via a factored sampling approach.