ElasticFusion: Dense SLAM Without A Pose Graph
Thomas Whelan,Stefan Leutenegger,Renato F. Salas-Moreno,Ben Glocker,Andrew J. Davison +4 more
- Vol. 11
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TLDR
This system is capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments explored using an RGB-D camera in an incremental online fashion, without pose graph optimisation or any postprocessing steps.Abstract:
We present a novel approach to real-time dense visual SLAM. Our system is capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments explored using an RGB-D camera in an incremental online fashion, without pose graph optimisation or any postprocessing steps. This is accomplished by using dense frame-tomodel camera tracking and windowed surfel-based fusion coupled with frequent model refinement through non-rigid surface deformations. Our approach applies local model-to-model surface loop closure optimisations as often as possible to stay close to the mode of the map distribution, while utilising global loop closure to recover from arbitrary drift and maintain global consistency.read more
Citations
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Proceedings ArticleDOI
ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes
TL;DR: This work introduces ScanNet, an RGB-D video dataset containing 2.5M views in 1513 scenes annotated with 3D camera poses, surface reconstructions, and semantic segmentations, and shows that using this data helps achieve state-of-the-art performance on several 3D scene understanding tasks.
Journal ArticleDOI
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José Neira,Ian Reid,John J. Leonard +7 more
TL;DR: Simultaneous localization and mapping (SLAM) as mentioned in this paper consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it.
Journal ArticleDOI
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José L. Neira,Ian Reid,John J. Leonard +7 more
TL;DR: What is now the de-facto standard formulation for SLAM is presented, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers.
Posted Content
ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes
TL;DR: The ScanNet dataset as discussed by the authors contains 2.5M RGB-D views in 1513 scenes annotated with 3D camera poses, surface reconstructions, and semantic segmentations.
Journal ArticleDOI
SVO: Semidirect Visual Odometry for Monocular and Multicamera Systems
TL;DR: A semidirect VO that uses direct methods to track and triangulate pixels that are characterized by high image gradients, but relies on proven feature-based methods for joint optimization of structure and motion is proposed.
References
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Proceedings ArticleDOI
KinectFusion: Real-time dense surface mapping and tracking
Richard Newcombe,Shahram Izadi,Otmar Hilliges,David Molyneaux,David Kim,Andrew J. Davison,Pushmeet Kohi,Jamie Shotton,Steve Hodges,Andrew Fitzgibbon +9 more
TL;DR: A system for accurate real-time mapping of complex and arbitrary indoor scenes in variable lighting conditions, using only a moving low-cost depth camera and commodity graphics hardware, which fuse all of the depth data streamed from a Kinect sensor into a single global implicit surface model of the observed scene in real- time.
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.
Proceedings ArticleDOI
A benchmark for the evaluation of RGB-D SLAM systems
TL;DR: A large set of image sequences from a Microsoft Kinect with highly accurate and time-synchronized ground truth camera poses from a motion capture system is recorded for the evaluation of RGB-D SLAM systems.
Proceedings ArticleDOI
DTAM: Dense tracking and mapping in real-time
TL;DR: It is demonstrated that a dense model permits superior tracking performance under rapid motion compared to a state of the art method using features; and the additional usefulness of the dense model for real-time scene interaction in a physics-enhanced augmented reality application is shown.