Title | ||
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Performance comparison of point feature detectors and descriptors for visual navigation on Android platform |
Abstract | ||
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Consumer electronics mobile devices, such like smartphones and tablets, are quickly growing in computing power and become equipped with advanced sensors. This makes a modern mobile device a viable platform for many computation-intensive, real-time applications. In this paper we present a study on the performance and robustness of point features detection and description in images acquired by a mobile device in the context of visual navigation. This is an important step towards infrastructure-less indoor self-localization and user guidance using only a smartphone or tablet. We rigorously evaluate the performance of several interest point detector and descriptor pairs on three different Android devices, using image sequences from publicly available robotics-related data sets, as well as our own data set obtained using a smartphone. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1109/IWCMC.2014.6906342 | Wireless Communications and Mobile Computing Conference |
Keywords | DocType | ISSN |
feature extraction,mobile computing,mobile robots,path planning,smart phones,Android platform,mobile device,performance comparison,point feature descriptors,point feature detectors,robotics-related data sets,smartphone,tablet computer,visual navigation,descriptors,detectors,mobile devices,point features | Conference | 2376-6492 |
Citations | PageRank | References |
4 | 0.41 | 14 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Michal Nowicki | 1 | 31 | 4.68 |
Piotr Skrzypczynski | 2 | 148 | 25.07 |