Name
Abstract | ||
|---|---|---|
In many practical applications of mobile devices self-localization of the user in a GPS-denied indoor environment is required. Among the available approaches the visual odometry concept enables continuous, precise egomotion estimation in previously unknown environments. In this paper we examine the usual pipeline of a monocular visual odometry system, identifying the bottlenecks and demonstrating how to circumvent the resource constrains, to implement a real-time visual odometry system on a smartphone or tablet. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-11755-3_48 | IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT II |
Keywords | Field | DocType |
Mobile device, Visual odometry, Self-localization | Computer vision,Self localization,Visual odometry,Computer science,Mobile device,Artificial intelligence,Feature based,Monocular | Conference |
Volume | ISSN | Citations |
8815 | 0302-9743 | 5 |
PageRank | References | Authors |
0.43 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Fularz | 1 | 17 | 5.13 |
| Michal Nowicki | 2 | 31 | 4.68 |
| Piotr Skrzypczynski | 3 | 148 | 25.07 |