CRIS Current Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishWe propose an effective, real-time solution to the RGB-D SLAM problem dubbed SlamDunk. Our proposal features a multi-view camera tracking approach based on a dynamic local map of the workspace, enables metric loop closure seamlessly and preserves local consistency by means of relative bundle adjustment principles. SlamDunk requires a few threads, low memory consumption and runs at 30Hz on a standard desktop computer without hardware acceleration by a GPGPU card. As such, it renders real-time dense SLAM affordable on commodity hardware. SlamDunk permits highly responsive interactive operation in a variety of workspaces and scenarios, such as scanning small objects or densely reconstructing large-scale environments. We provide quantitative and qualitative experiments in diverse settings to demonstrate the accuracy and robustness of the proposed approach.
| Titolo: | SlamDunk: Affordable Real-Time RGB-D SLAM | |
| Autore/i: | FIORAIO, NICOLA; DI STEFANO, LUIGI | |
| Autore/i Unibo: | ||
| Anno: | 2015 | |
| Titolo del libro: | Computer Vision - ECCV 2014 Workshops | |
| Pagina iniziale: | 401 | |
| Pagina finale: | 414 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-319-16178-5_28 | |
| Abstract: | We propose an effective, real-time solution to the RGB-D SLAM problem dubbed SlamDunk. Our proposal features a multi-view camera tracking approach based on a dynamic local map of the workspace, enables metric loop closure seamlessly and preserves local consistency by means of relative bundle adjustment principles. SlamDunk requires a few threads, low memory consumption and runs at 30Hz on a standard desktop computer without hardware acceleration by a GPGPU card. As such, it renders real-time dense SLAM affordable on commodity hardware. SlamDunk permits highly responsive interactive operation in a variety of workspaces and scenarios, such as scanning small objects or densely reconstructing large-scale environments. We provide quantitative and qualitative experiments in diverse settings to demonstrate the accuracy and robustness of the proposed approach. | |
| Data stato definitivo: | 25-gen-2016 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11585/383075
Copyright © 2022